SVO Pro: Semi-direct Visual-Inertial Odometry and SLAM
for Monocular, Stereo, and Wide Angle Cameras,
HTML Version.
WWW Link.
2111
Code, Visual Odometry. Includes:
Visual-odometry: The most recent version of SVO that supports
perspective and fisheye/catadioptric cameras in monocular or stereo
setup. It also includes active exposure control. Visual-inertial
odometry: SVO fronted + visual-inertial sliding window optimization
backend (modified from OKVIS) Visual-inertial SLAM: SVO frontend +
visual-inertial sliding window optimization backend + globally bundle
adjusted map (using iSAM2). The global map is updated in real-time,
thanks to iSAM2, and used for localization at frame-rate.
Visual-inertial SLAM with loop closure: Loop closures, via DBoW2, are
integrated in the global bundle adjustment. Pose graph optimization is
also included as a lightweight replacement of the global bundle
adjustment.
Adam, A.,
Rivlin, E.[Ehud],
Rotstein, H.P.[Héctor P.],
Fusion of Fixation and Odometry for Vehicle Navigation,
SMC-A(29), No. 6, November 1999, pp. 593.
IEEE Top Reference.
BibRef
9911
Scaramuzza, D.[Davide],
1-Point-RANSAC Structure from Motion for Vehicle-Mounted Cameras by
Exploiting Non-holonomic Constraints,
IJCV(95), No. 1, October 2011, pp. 74-85.
WWW Link.
1108
BibRef
Scaramuzza, D.[Davide],
Siegwart, R.[Roland],
Monocular Omnidirectional Visual Odometry for Outdoor Ground Vehicles,
CVS08(xx-yy).
Springer DOI
0805
BibRef
Scaramuzza, D.[Davide],
Fraundorfer, F.[Friedrich],
Pollefeys, M.[Marc],
Siegwart, R.[Roland],
Absolute scale in structure from motion from a single vehicle mounted
camera by exploiting nonholonomic constraints,
ICCV09(1413-1419).
IEEE DOI
0909
BibRef
Scaramuzza, D.[Davide],
Fraundorfer, F.[Friedrich],
Siegwart, R.[Roland],
Pollefeys, M.[Marc],
Closing the Loop in Appearance Guided SfM for Omnidirectional Cameras,
OMNIVIS08(xx-yy).
0810
BibRef
Martinelli, A.[Agostino],
Closed-Form Solution of Visual-Inertial Structure from Motion,
IJCV(106), No. 2, January 2014, pp. 138-152.
WWW Link.
1402
BibRef
Scaramuzza, D.[Davide],
Martinelli, A.[Agostino],
Siegwart, R.[Roland],
A Flexible Technique for Accurate Omnidirectional Camera Calibration
and Structure from Motion,
CVS06(45).
IEEE DOI
0602
BibRef
Kneip, L.[Laurent],
Chli, M.[Margarita],
Siegwart, R.[Roland],
Robust Real-Time Visual Odometry with a Single Camera and an IMU,
BMVC11(xx-yy).
HTML Version.
1110
BibRef
Parra Alonso, I.,
Llorca, D.F.,
Gavilan, M.,
Pardo, S.Á.,
Garcia-Garrido, M.Á.,
Vlacic, L.,
Sotelo, M.Á.,
Accurate Global Localization Using Visual Odometry and Digital Maps on
Urban Environments,
ITS(13), No. 4, December 2012, pp. 1535-1545.
IEEE DOI
1212
BibRef
Naroditsky, O.[Oleg],
Zhou, X.S.[Xun S.],
Gallier, J.[Jean],
Roumeliotis, S.I.[Stergios I.],
Daniilidis, K.[Kostas],
Two Efficient Solutions for Visual Odometry Using Directional
Correspondence,
PAMI(34), No. 4, April 2012, pp. 818-824.
IEEE DOI
1203
Two-view, relative pose from 3 image points and one common direction
(e.g. vanishing point or gravity)
BibRef
Hesch, J.A.[Joel A.],
Mourikis, A.I.[Anastasios I.],
Roumeliotis, S.I.[Stergios I.],
Extrinsic Camera Calibration Using Multiple Reflections,
ECCV10(IV: 311-325).
Springer DOI
1009
BibRef
Mourikis, A.I.[Anastasios I.],
Roumeliotis, S.I.[Stergios I.],
A dual-layer estimator architecture for long-term localization,
VisLoc08(1-8).
IEEE DOI
0806
BibRef
Siddiqui, R.,
Khatibi, S.,
Robust visual odometry estimation of road vehicle from dominant
surfaces for large-scale mapping,
IET-ITS(9), No. 3, 2015, pp. 314-322.
DOI Link
1506
cameras
BibRef
Mouats, T.,
Aouf, N.,
Sappa, A.D.,
Aguilera, C.,
Toledo, R.,
Multispectral Stereo Odometry,
ITS(16), No. 3, June 2015, pp. 1210-1224.
IEEE DOI
1506
Cameras
BibRef
De-Maeztu, L.[Leonardo],
Elordi, U.[Unai],
Nieto, M.[Marcos],
Barandiaran, J.[Javier],
Otaegui, O.[Oihana],
A temporally consistent grid-based visual odometry framework for
multi-core architectures,
RealTimeIP(10), No. 4, December 2015, pp. 759-769.
Springer DOI
1512
BibRef
Brubaker, M.A.[Marcus A.],
Geiger, A.[Andreas],
Urtasun, R.[Raquel],
Map-Based Probabilistic Visual Self-Localization,
PAMI(38), No. 4, April 2016, pp. 652-665.
IEEE DOI
1603
BibRef
Earlier:
Lost! Leveraging the Crowd for Probabilistic Visual Self-Localization,
CVPR13(3057-3064)
IEEE DOI
1309
Award, CVPR, HM. Computational modeling.
localization; mixture model; Using visual odometry and road maps.
BibRef
Güney, F.[Fatma],
Geiger, A.[Andreas],
Deep Discrete Flow,
ACCV16(IV: 207-224).
Springer DOI
1704
BibRef
Menze, M.[Moritz],
Heipke, C.[Christian],
Geiger, A.[Andreas],
Object Scene Flow,
PandRS(140), 2018, pp. 60-76.
Elsevier DOI
1805
BibRef
Earlier:
Discrete Optimization for Optical Flow,
GCPR15(16-28).
Springer DOI
1511
BibRef
Earlier: A1, A3, Only:
Object scene flow for autonomous vehicles,
CVPR15(3061-3070)
IEEE DOI
1510
Scene flow, Motion estimation, Motion segmentation,
3D reconstruction, Active Shape Model, Object detection
BibRef
Song, S.Y.[Shi-Yu],
Chandraker, M.[Manmohan],
Guest, C.C.,
High Accuracy Monocular SFM and Scale Correction for Autonomous
Driving,
PAMI(38), No. 4, April 2016, pp. 730-743.
IEEE DOI
1603
Accuracy
BibRef
Song, S.Y.[Shi-Yu],
Chandraker, M.[Manmohan],
Joint SFM and detection cues for monocular 3D localization in road
scenes,
CVPR15(3734-3742)
IEEE DOI
1510
BibRef
Eslami, H.[Hamed],
Raie, A.A.[Abolghasem A.],
Faez, K.[Karim],
Precise Vehicle Speed Measurement Based on a Hierarchical Homographic
Transform Estimation for Law Enforcement Applications,
IEICE(E99-D), No. 6, June 2016, pp. 1635-1644.
WWW Link.
1606
BibRef
Borges, P.V.K.,
Vidas, S.,
Practical Infrared Visual Odometry,
ITS(17), No. 8, August 2016, pp. 2205-2213.
IEEE DOI
1608
Cameras
BibRef
Lentaris, G.,
Stamoulias, I.,
Soudris, D.,
Lourakis, M.,
HW/SW Codesign and FPGA Acceleration of Visual Odometry Algorithms
for Rover Navigation on Mars,
CirSysVideo(26), No. 8, August 2016, pp. 1563-1577.
IEEE DOI
1609
computer vision
BibRef
Fanfani, M.[Marco],
Bellavia, F.[Fabio],
Colombo, C.[Carlo],
Accurate keyframe selection and keypoint tracking for robust visual
odometry,
MVA(27), No. 5, August 2016, pp. 833-844.
WWW Link.
1609
BibRef
Fanfani, M.[Marco],
Colombo, C.[Carlo],
Bellavia, F.[Fabio],
Restoration and Enhancement of Historical Stereo Photos Through Optical
Flow,
FAPER20(643-656).
Springer DOI
2103
BibRef
Wu, M.,
Lam, S.K.,
Srikanthan, T.,
A Framework for Fast and Robust Visual Odometry,
ITS(18), No. 12, December 2017, pp. 3433-3448.
IEEE DOI
1712
Computational complexity, Estimation, Feature extraction,
Motion estimation, Robustness, Tracking, ADASs, Visual odometry,
motion estimation
BibRef
Yang, S.,
Jiang, R.,
Wang, H.,
Ge, S.S.,
Road Constrained Monocular Visual Localization Using
Gaussian-Gaussian Cloud Model,
ITS(18), No. 12, December 2017, pp. 3449-3456.
IEEE DOI
1712
Cameras, Hidden Markov models, Mathematical model,
Measurement uncertainty, Roads, Shape, Visualization,
monocular visual odometry (MVO)
BibRef
Engel, J.[Jakob],
Koltun, V.[Vladlen],
Cremers, D.[Daniel],
Direct Sparse Odometry,
PAMI(40), No. 3, March 2018, pp. 611-625.
IEEE DOI
1802
Cameras, Computational modeling, Geometry, Optimization, Robustness,
Visualization, Visual odometry, SLAM,
structure from motion
BibRef
Engel, J.[Jakob],
Sturm, J.[Jurgen],
Cremers, D.[Daniel],
Semi-dense Visual Odometry for a Monocular Camera,
ICCV13(1449-1456)
IEEE DOI
1403
SLAM; dense; monocular; stereo; visual odometry
BibRef
Birem, M.[Merwan],
Kleihorst, R.[Richard],
El-Ghouti, N.[Norddin],
Visual odometry based on the Fourier transform using a monocular
ground-facing camera,
RealTimeIP(14), No. 3, March 2018, pp. 637-646.
WWW Link.
1804
BibRef
Alexander, E.[Emma],
Guo, Q.[Qi],
Koppal, S.[Sanjeev],
Gortler, S.J.[Steven J.],
Zickler, T.[Todd],
Focal Flow: Velocity and Depth from Differential Defocus Through Motion,
IJCV(126), No. 10, October 2018, pp. 1062-1083.
Springer DOI
1809
BibRef
Earlier:
Focal Flow: Measuring Distance and Velocity with Defocus and
Differential Motion,
ECCV16(III: 667-682).
Springer DOI
1611
BibRef
Guo, Q.[Qi],
Alexander, E.[Emma],
Zickler, T.[Todd],
Focal Track:
Depth and Accommodation with Oscillating Lens Deformation,
ICCV17(966-974)
IEEE DOI
1802
Lenses, Mathematical model, Optical imaging, Optical sensors,
Oscillators, Robot sensing systems, Strain
BibRef
Pereira, F.I.,
Luft, J.A.,
Ilha, G.,
Susin, A.,
A Novel Resection-Intersection Algorithm With Fast Triangulation
Applied to Monocular Visual Odometry,
ITS(19), No. 11, November 2018, pp. 3584-3593.
IEEE DOI
1812
cameras, distance measurement,
image motion analysis, image reconstruction, minimisation,
bundle-adjustment
BibRef
Vidal, A.R.[Antoni Rosinol],
Rebecq, H.[Henri],
Horstschaefer, T.[Timo],
Scaramuzza, D.[Davide],
Ultimate SLAM? Combining Events, Images, and IMU for
Robust Visual SLAM in HDR and High Speed Scenarios,
RALetters(3), No. 2, 2018
IEEE DOI
PDF File.
BibRef
1800
Earlier: A2, A3, A4, Only:
Real-time Visual-Inertial Odometry for Event Cameras using
Keyframe-based Nonlinear Optimization,
BMVC17(xx-yy).
PDF File. For code:
WWW Link.
BibRef
Guo, R.B.[Rui-Bin],
Zhou, D.X.[Dong-Xiang],
Peng, K.J.[Ke-Ju],
Liu, Y.H.[Yun-Hui],
Fast Visual Odometry Based Sparse Geometric Constraint for RGB-D Camera,
IEICE(E102-D), No. 1, January 2019, pp. 214-218.
WWW Link.
1901
BibRef
Yoon, S.J.[Sung-Joo],
Kim, T.[Taejung],
Development of Stereo Visual Odometry Based on Photogrammetric
Feature Optimization,
RS(11), No. 1, 2019, pp. xx-yy.
DOI Link
1901
BibRef
Salleh, D.N.S.D.A.[Dayang Nur Salmi Dharmiza Awang],
Seignez, E.[Emmanuel],
Longitudinal error improvement by visual odometry trajectory trail and
road segment matching,
IET-ITS(13), No. 2, February 2019, pp. 313-322.
DOI Link
1902
BibRef
Wang, Y.D.[Yan-Dong],
Zhang, T.[Tao],
Wang, Y.C.[Yuan-Chao],
Ma, J.W.[Jing-Wei],
Li, Y.H.[Yan-Hui],
Han, J.Z.[Jing-Zhuang],
Compass aided visual-inertial odometry,
JVCIR(60), 2019, pp. 101-115.
Elsevier DOI
1903
Visual-inertial odometry (VIO), Compass,
Sliding window estimator, Inconsistency, Pre-integration, Minimum cost function
BibRef
Zheng, F.,
Tang, H.,
Liu, Y.,
Odometry-Vision-Based Ground Vehicle Motion Estimation With
SE(2)-Constrained SE(3) Poses,
Cyber(49), No. 7, July 2019, pp. 2652-2663.
IEEE DOI
1905
Visualization, Optimization, Motion estimation, Estimation,
Land vehicles, Manifolds, Sensors, Mobile robots,
sensor fusion, state estimation
BibRef
Lee, C.R.[Chang-Ryeol],
Yoon, K.J.[Kuk-Jin],
Confidence analysis of feature points for visual-inertial odometry of
urban vehicles,
IET-ITS(13), No. 7, July 2019, pp. 1130-1138.
DOI Link
1906
BibRef
Heo, S.,
Cha, J.,
Park, C.G.,
EKF-Based Visual Inertial Navigation Using Sliding Window Nonlinear
Optimization,
ITS(20), No. 7, July 2019, pp. 2470-2479.
IEEE DOI
1907
Cameras, Visualization, Measurement uncertainty,
Simultaneous localization and mapping, Optimization, Estimation,
visual-inertial odometry
BibRef
Nejad, Z.Z.[Zana Zakaryaie],
Ahmadabadian, A.H.[Ali Hosseininaveh],
ARM-VO: an efficient monocular visual odometry for ground vehicles on
ARM CPUs,
MVA(30), No. 6, September 2019, pp. 1061-1070.
WWW Link.
1909
BibRef
Alletto, S.[Stefano],
Abati, D.[Davide],
Calderara, S.[Simone],
Cucchiara, R.[Rita],
Rigazio, L.[Luca],
Self-Supervised Optical Flow Estimation by Projective Bootstrap,
ITS(20), No. 9, September 2019, pp. 3294-3302.
IEEE DOI
1909
Optical imaging, Estimation, Adaptive optics, Optical sensors,
Automotive engineering, Cameras, Computer architecture,
unsupervised learning
BibRef
Jurevicius, R.[Rokas],
Marcinkevicius, V.[Virginijus],
Šeibokas, J.[Justinas],
Robust GNSS-denied localization for UAV using particle filter and
visual odometry,
MVA(30), No. 7-8, October 2019, pp. 1181-1190.
Springer DOI
1911
BibRef
Jaramillo, C.[Carlos],
Yang, L.[Liang],
Muñoz, J.P.[J. Pablo],
Taguchi, Y.[Yuichi],
Xiao, J.Z.[Ji-Zhong],
Visual odometry with a single-camera stereo omnidirectional system,
MVA(30), No. 7-8, October 2019, pp. 1145-1155.
Springer DOI
1911
BibRef
Angladon, V.[Vincent],
Gasparini, S.[Simone],
Charvillat, V.[Vincent],
Pribanic, T.[Tomislav],
Petkovic, T.[Tomislav],
Ðonlic, M.[Matea],
Ahsan, B.[Benjamin],
Bruel, F.[Frédéric],
An evaluation of real-time RGB-D visual odometry algorithms on mobile
devices,
RealTimeIP(16), No. 5, October 2019, pp. 1643-1660.
Springer DOI
1911
BibRef
Piao, J.,
Kim, S.,
Real-Time Visual-Inertial SLAM Based on Adaptive Keyframe Selection
for Mobile AR Applications,
MultMed(21), No. 11, November 2019, pp. 2827-2836.
IEEE DOI
1911
Simultaneous localization and mapping, Cameras,
Feature extraction, Tracking, Mobile handsets, Real-time systems,
visual-inertial odometry
BibRef
Gao, Z.[Zhi],
Ramesh, B.[Bharath],
Lin, W.Y.[Wen-Yan],
Wang, P.F.[Peng-Fei],
Yan, X.[Xu],
Zhai, R.F.[Rui-Fang],
Efficient velocity estimation for MAVs by fusing motion from two
frontally parallel cameras,
RealTimeIP(16), No. 6, December 2019, pp. 2367-2378.
Springer DOI
1912
BibRef
Low, W.F.,
Gao, Z.,
Xiang, C.,
Ramesh, B.,
SOFEA: A Non-iterative and Robust Optical Flow Estimation Algorithm
for Dynamic Vision Sensors,
PBVS20(368-377)
IEEE DOI
2008
Estimation, Voltage control, Streaming media, Cameras,
Optical sensors, Optical flow
BibRef
Qin, J.Y.[Jiang-Ying],
Li, M.[Ming],
Liao, X.[Xuan],
Zhong, J.G.[Jia-Geng],
Accumulative Errors Optimization for Visual Odometry of ORB-SLAM2
Based on RGB-D Cameras,
IJGI(8), No. 12, 2019, pp. xx-yy.
DOI Link
1912
BibRef
Zhou, D.,
Dai, Y.,
Li, H.,
Ground-Plane-Based Absolute Scale Estimation for Monocular Visual
Odometry,
ITS(21), No. 2, February 2020, pp. 791-802.
IEEE DOI
2002
Cameras, Estimation, Simultaneous localization and mapping,
Sensor systems, Laser radar,
monocular VO and SLAM
BibRef
Wang, A.,
Fang, Z.,
Gao, Y.,
Tan, S.,
Wang, S.,
Ma, S.,
Hwang, J.,
Adversarial Learning for Joint Optimization of Depth and Ego-Motion,
IP(29), 2020, pp. 4130-4142.
IEEE DOI
2002
Depth estimation, ego-motion, self-supervised,
adversarial learning, direct visual odometry
BibRef
He, M.[Ming],
Zhu, C.Z.[Chao-Zheng],
Huang, Q.[Qian],
Ren, B.[Baosen],
Liu, J.T.[Jin-Tao],
A review of monocular visual odometry,
VC(36), No. 5, May 2020, pp. 1053-1065.
Springer DOI
2005
Survey, Visual Odometry.
BibRef
Dong, X.,
Dong, X.,
Dong, J.,
Zhou, H.,
Monocular Visual-IMU Odometry: A Comparative Evaluation of
Detector-Descriptor-Based Methods,
ITS(21), No. 6, June 2020, pp. 2471-2484.
IEEE DOI
2006
Detectors, Feature extraction, Visualization, Roads, Task analysis,
Clutter, Shape, Evaluation, odometry, monocular visual-IMU odometry,
salient point detectors
BibRef
Xu, B.[Bo],
Chen, Y.[Yu],
Zhang, S.J.[Shou-Jian],
Wang, J.R.[Jing-Rong],
Improved Point-Line Visual-Inertial Odometry System Using Helmert
Variance Component Estimation,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link
2009
BibRef
Arbabmir, M.[Mohammadvali],
Ebrahimi, M.[Masoud],
Simultaneous filter tuning and calibration of the camera and inertial
measurement unit camera for a vision inertial navigation system,
IET-IPR(14), No. 12, October 2020, pp. 2756-2767.
DOI Link
2010
BibRef
Wang, Y.[YuAn],
Chen, L.[Liang],
Wei, P.[Peng],
Lu, X.C.[Xiang-Chen],
Visual-Inertial Odometry of Smartphone under Manhattan World,
RS(12), No. 22, 2020, pp. xx-yy.
DOI Link
2011
BibRef
Liu, J.,
Qiu, X.,
Ding, C.,
The First Attempt of SAR Visual-Inertial Odometry,
GeoRS(59), No. 1, January 2021, pp. 287-304.
IEEE DOI
2012
Synthetic aperture radar, Imaging,
Simultaneous localization and mapping, Visual odometry,
track optimization
BibRef
Micusik, B.[Branislav],
Evangelidis, G.[Georgios],
Renormalization for Initialization of Rolling Shutter Visual-Inertial
Odometry,
IJCV(129), No. 6, June 2021, pp. 2011-2027.
Springer DOI
2106
BibRef
Lu, J.X.[Jun-Xin],
Fang, Z.J.[Zhi-Jun],
Gao, Y.B.[Yong-Bin],
Chen, J.Y.[Jie-Yu],
Line-based visual odometry using local gradient fitting,
JVCIR(77), 2021, pp. 103071.
Elsevier DOI
2106
Visual odometry, Line, Gradient, Texture-less, RGB-D
BibRef
Zhang, J.C.[Jia-Chen],
Wen, W.S.[Wei-Song],
Huang, F.[Feng],
Chen, X.D.[Xiao-Dong],
Hsu, L.T.[Li-Ta],
Coarse-to-Fine Loosely-Coupled LiDAR-Inertial Odometry for Urban
Positioning and Mapping,
RS(13), No. 12, 2021, pp. xx-yy.
DOI Link
2106
BibRef
Peng, J.Q.[Jing-Quan],
Liu, Y.Q.[Yan-Qing],
Jiang, H.C.[Hao-Chen],
Semantic and edge-based visual odometry by joint minimizing semantic
and edge distance error,
IVC(113), 2021, pp. 104240.
Elsevier DOI
2108
Edge-based visual odometry,
Semantic visual odometry distance transform (DT), Semantic segmentation
BibRef
Gong, X.X.[Xiao-Xi],
Liu, Y.P.[Yuan-Peng],
Wu, Q.Y.[Qiao-Yun],
Huang, J.[Jiayi],
Zong, H.[Hua],
Wang, J.[Jun],
An Accurate, Robust Visual Odometry and Detail-Preserving
Reconstruction System,
MultMed(23), 2021, pp. 2820-2832.
IEEE DOI
2109
Image reconstruction, Estimation, Cameras, Tracking, Visual odometry,
Simultaneous localization and mapping, Brightness,
visual odometry
BibRef
Kim, U.H.[Ue-Hwan],
Kim, S.H.[Se-Ho],
Kim, J.H.[Jong-Hwan],
SimVODIS: Simultaneous Visual Odometry, Object Detection, and
Instance Segmentation,
PAMI(44), No. 1, January 2022, pp. 428-441.
IEEE DOI
2112
Semantics, Task analysis, Training, Intelligent agents,
Feature extraction, Object detection, Instruction sets,
deep convolutional neural network (CNN)
BibRef
Liu, H.[Hao],
Huang, D.D.[Dan Dan],
Geng, Z.Y.[Zhen Ye],
Visual Odometry Algorithm Based on Deep Learning,
ICIVC21(322-327)
IEEE DOI
2112
Deep learning, Training, Visualization,
Simultaneous localization and mapping, Trajectory tracking,
multi-task learning
BibRef
Xue, F.[Fei],
Wang, X.[Xin],
Wang, J.Q.[Jun-Qiu],
Zha, H.B.[Hong-Bin],
Deep Visual Odometry With Adaptive Memory,
PAMI(44), No. 2, February 2022, pp. 940-954.
IEEE DOI
2201
Cameras, Task analysis, Tracking,
Simultaneous localization and mapping, Pose estimation, History,
attention
BibRef
Li, S.K.[Shun-Kai],
Wu, X.[Xin],
Cao, Y.D.[Ying-Dian],
Zha, H.B.[Hong-Bin],
Generalizing to the Open World: Deep Visual Odometry with Online
Adaptation,
CVPR21(13179-13188)
IEEE DOI
2111
Training, Optical filters, Uncertainty, Pose estimation,
Bayes methods, Pattern recognition, Optimization
BibRef
Li, S.K.[Shun-Kai],
Wang, X.[Xin],
Cao, Y.D.[Ying-Dian],
Xue, F.[Fei],
Yan, Z.[Zike],
Zha, H.B.[Hong-Bin],
Self-Supervised Deep Visual Odometry With Online Adaptation,
CVPR20(6338-6347)
IEEE DOI
2008
BibRef
Earlier: A1, A4, A2, A5, A6, Only:
Sequential Adversarial Learning for Self-Supervised Deep Visual
Odometry,
ICCV19(2851-2860)
IEEE DOI
2004
Training, Adaptation models, Training data, Task analysis,
Estimation, Machine learning, Convergence.
image classification, image representation, image segmentation,
learning (artificial intelligence), neural nets,
Optical variables control
BibRef
Yang, B.C.[Bin-Chao],
Xu, X.Y.[Xin-Ying],
Ren, J.C.[Jin-Chang],
Cheng, L.[Lan],
Guo, L.[Lei],
Zhang, Z.[Zhe],
SAM-Net: Semantic probabilistic and attention mechanisms of dynamic
objects for self-supervised depth and camera pose estimation in
visual odometry applications,
PRL(153), 2022, pp. 126-135.
Elsevier DOI
2201
Visual odometry, Self-supervised deep learning,
Object detection, Semantic probabilistic map, Attention mechanism
BibRef
Eising, C.[Ciarán],
Pereira, L.F.[Leroy-Francisco],
Horgan, J.[Jonathan],
Selvaraju, A.[Anbuchezhiyan],
McDonald, J.[John],
Moran, P.[Paul],
2.5D vehicle odometry estimation,
IET-ITS(16), No. 3, 2022, pp. 292-308.
DOI Link
2202
BibRef
He, X.[Xuan],
Gao, W.[Wang],
Sheng, C.Z.[Chuan-Zhen],
Zhang, Z.T.[Zi-Teng],
Pan, S.[Shuguo],
Duan, L.J.[Li-Jin],
Zhang, H.[Hui],
Lu, X.Y.[Xin-Yu],
LiDAR-Visual-Inertial Odometry Based on Optimized Visual Point-Line
Features,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link
2202
BibRef
Wan, Y.C.[Ying-Cai],
Zhao, Q.K.[Qian-Kun],
Guo, C.[Cheng],
Xu, C.L.[Chen-Long],
Fang, L.J.[Li-Jing],
Multi-Sensor Fusion Self-Supervised Deep Odometry and Depth
Estimation,
RS(14), No. 5, 2022, pp. xx-yy.
DOI Link
2203
BibRef
Fang, X.[Xu],
Li, Q.[Qing],
Li, Q.Q.[Qing-Quan],
Ding, K.[Kai],
Zhu, J.[Jiasong],
Exploiting Graph and Geodesic Distance Constraint for Deep
Learning-Based Visual Odometry,
RS(14), No. 8, 2022, pp. xx-yy.
DOI Link
2205
BibRef
Paolillo, G.[Gerardo],
Astarita, T.[Tommaso],
Perspective Camera Model With Refraction Correction for Optical
Velocimetry Measurements in Complex Geometries,
PAMI(44), No. 6, June 2022, pp. 3185-3196.
IEEE DOI
2205
Cameras, Optical distortion, Distortion, Calibration, Solid modeling,
Ray tracing, Geometry, Camera calibration, flow visualization,
refractive geometry
BibRef
Liu, Y.L.[Yi-Ling],
Wang, H.S.[He-Sheng],
Wang, J.C.[Jing-Chuan],
Wang, X.L.[Xin-Lei],
Unsupervised Monocular Visual Odometry Based on Confidence Evaluation,
ITS(23), No. 6, June 2022, pp. 5387-5396.
IEEE DOI
2206
Visual odometry, Pose estimation, Feature extraction, Cameras,
Visualization, Trajectory, Optimization, pose estimation,
visual odometry
BibRef
Zhang, H.[Hui],
Wang, X.W.[Xiang-Wei],
Yin, X.C.[Xiao-Chuan],
Du, M.X.[Ming-Xiao],
Liu, C.J.[Cheng-Ju],
Chen, Q.J.[Qi-Jun],
Geometry-Constrained Scale Estimation for Monocular Visual Odometry,
MultMed(24), 2022, pp. 3144-3156.
IEEE DOI
2206
Roads, Cameras, Estimation, Visual odometry, Robots, Visualization,
Measurement, Monocular visual odometry, scale recovery, geometry-constrained
BibRef
Zhao, C.Q.[Chao-Qiang],
Tang, Y.[Yang],
Sun, Q.[Qiyu],
Vasilakos, A.V.[Athanasios V.],
Deep Direct Visual Odometry,
ITS(23), No. 7, July 2022, pp. 7733-7742.
IEEE DOI
2207
Training, Trajectory, Deep learning, Visual odometry, Tracking,
Pose estimation, Visualization, Visual odometry, direct methods,
unsupervised learning
BibRef
Jia, S.C.[Shao-Cheng],
Pei, X.[Xin],
Jing, X.[Xiao],
Yao, D.[Danya],
Self-Supervised 3D Reconstruction and Ego-Motion Estimation Via
On-Board Monocular Video,
ITS(23), No. 7, July 2022, pp. 7557-7569.
IEEE DOI
2207
Estimation, Uncertainty, Training, Safety, Laser radar,
Matrix converters, 3D reconstruction, monocular depth estimation,
visual odometry
BibRef
Ju, X.L.[Xiao-Liang],
Xu, D.H.[Dong-Hao],
Zhao, H.J.[Hui-Jing],
Scene-Aware Error Modeling of LiDAR/Visual Odometry for Fusion-Based
Vehicle Localization,
ITS(23), No. 7, July 2022, pp. 6480-6494.
IEEE DOI
2207
Location awareness, Laser radar, Visual odometry,
Measurement uncertainty, Sensors, Cameras, Uncertainty, Localization,
fusion
BibRef
Beauvisage, A.[Axel],
Ahiska, K.[Kenan],
Aouf, N.[Nabil],
Robust Multispectral Visual-Inertial Navigation With Visual Odometry
Failure Recovery,
ITS(23), No. 7, July 2022, pp. 9089-9101.
IEEE DOI
2207
Cameras, Visualization, Visual odometry, Sensors, Sensor systems,
Measurement, Image sensors, Multispectral, infrared imaging,
VINS
BibRef
Azimi, A.[Arash],
Hosseininaveh-Ahmadabadian, A.[Ali],
Remondino, F.[Fabio],
PKS: A photogrammetric key-frame selection method for visual-inertial
systems built on ORB-SLAM3,
PandRS(191), 2022, pp. 18-32.
Elsevier DOI
2208
Visual Odometry, Visual SLAM, Key-Frame Selection,
Visual-Inertial Systems, Inertial Measurement Unit (IMU),
Photogrammetric Key-Frame Selection
BibRef
Zhang, S.[Sen],
Zhang, J.[Jing],
Tao, D.C.[Da-Cheng],
Information-Theoretic Odometry Learning,
IJCV(130), No. 11, November 2022, pp. 2553-2570.
Springer DOI
2210
BibRef
Wang, Y.S.[Yi-Shen],
Zhang, S.M.[Shao-Ming],
Wang, J.M.[Jian-Mei],
Ceiling-View Semi-Direct Monocular Visual Odometry with Planar
Constraint,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link
2212
BibRef
Polizzi, V.[Vincenzo],
Hewitt, R.[Robert],
Hidalgo-Carrió, J.[Javier],
Delaune, J.[Jeff],
Scaramuzza, D.[Davide],
Data-Efficient Collaborative Decentralized Thermal-Inertial Odometry,
RALetters(7), No. 4, 2022, pp. 10681-10688.
IEEE DOI
Code, Odometry.
HTML Version.
BibRef
2200
Cao, Y.J.[Yi-Jun],
Zhang, X.S.[Xian-Shi],
Luo, F.Y.[Fu-Ya],
Peng, P.[Peng],
Lin, C.[Chuan],
Yang, K.F.[Kai-Fu],
Li, Y.J.[Yong-Jie],
Learning generalized visual odometry using position-aware optical
flow and geometric bundle adjustment,
PR(136), 2023, pp. 109262.
Elsevier DOI
2301
Visual odometry, Self-supervise learning, Optical flow,
Monocular depth estimation, Joint learning, Generalization capability
BibRef
Dai, J.J.[Jia-Jia],
Gong, X.X.[Xiao-Xi],
Li, Y.[Yida],
Wang, J.[Jun],
Wei, M.Q.[Ming-Qiang],
Self-Supervised Deep Visual Odometry Based on Geometric Attention
Model,
ITS(24), No. 3, March 2023, pp. 3157-3166.
IEEE DOI
2303
Estimation, Cameras, Optical imaging, Feature extraction,
Adaptive optics, Training, Visual odometry, Visual odometry,
pose graph optimization
BibRef
Gao, Y.X.[Yuan-Xi],
Yuan, J.[Jing],
Jiang, J.Q.[Jing-Qi],
Sun, Q.X.[Qin-Xuan],
Zhang, X.[Xuebo],
VIDO: A Robust and Consistent Monocular Visual-Inertial-Depth
Odometry,
ITS(24), No. 3, March 2023, pp. 2976-2992.
IEEE DOI
2303
Location awareness, Visualization,
Simultaneous localization and mapping, Pose estimation,
visual-inertial subsystem
BibRef
Wang, Z.W.[Zhi-Wei],
Pang, B.[Bao],
Song, Y.[Yong],
Yuan, X.F.[Xian-Feng],
Xu, Q.Y.[Qing-Yang],
Li, Y.[Yibin],
Robust Visual-Inertial Odometry Based on a Kalman Filter and Factor
Graph,
ITS(24), No. 7, July 2023, pp. 7048-7060.
IEEE DOI
2307
Simultaneous localization and mapping, State estimation,
Kalman filters, Visualization, Real-time systems, visual-inertial odometry
BibRef
Cao, Y.J.[Yi-Jun],
Zhang, X.S.[Xian-Shi],
Luo, F.[Fuya],
Lin, C.[Chuan],
Li, Y.J.[Yong-Jie],
Unsupervised Visual Odometry and Action Integration for PointGoal
Navigation in Indoor Environment,
CirSysVideo(33), No. 10, October 2023, pp. 6173-6184.
IEEE DOI
2310
BibRef
Kim, C.Y.[Changh-Yeon],
Jang, Y.[Youngseok],
Kim, J.[Junha],
Kim, P.[Pyojin],
Kim, H.J.[H. Jin],
Scale-Aware Monocular Visual Odometry and Extrinsic Calibration Using
Vehicle Kinematics,
ITS(24), No. 12, December 2023, pp. 14757-14771.
IEEE DOI
2312
BibRef
Wang, J.[Jun],
Gu, P.F.[Peng-Fei],
Wang, L.[Lei],
Meng, Z.Y.[Zi-Yang],
RVIO: An Effective Localization Algorithm for Range-Aided
Visual-Inertial Odometry System,
ITS(25), No. 2, February 2024, pp. 1476-1490.
IEEE DOI
2402
Location awareness, Cameras, Optimization, Robot sensing systems,
Odometry, Observability, Robot kinematics, particle filter
BibRef
Mollica, G.[Giuseppe],
Felicioni, S.[Simone],
Legittimo, M.[Marco],
Meli, L.[Leonardo],
Costante, G.[Gabriele],
Valigi, P.[Paolo],
MA-VIED: A Multisensor Automotive Visual Inertial Event Dataset,
ITS(25), No. 1, January 2024, pp. 214-224.
IEEE DOI
2402
Cameras, Sensors, Wheels, Sensor fusion, Odometry, Standards,
Visualization, Visual inertial odometry, event vision,
sensor fusion
BibRef
Song, X.G.[Xiao-Gang],
Hu, H.Y.[Hao-Yue],
Liang, L.[Li],
Shi, W.W.[Wei-Wei],
Xie, G.[Guo],
Lu, X.F.[Xiao-Feng],
Hei, X.H.[Xin-Hong],
Unsupervised Monocular Estimation of Depth and Visual Odometry Using
Attention and Depth-Pose Consistency Loss,
MultMed(26), 2024, pp. 3517-3529.
IEEE DOI
2402
Estimation, Feature extraction, Training, Image reconstruction,
Deep learning, Convolution, Cameras, Unsupervised learning,
attention
BibRef
Han, S.[Songrui],
Li, M.[Mingchi],
Tang, H.Y.[Hong-Ying],
Song, Y.Z.[Yao-Zhe],
Tong, G.[Guanjun],
UVMO: Deep unsupervised visual reconstruction-based
multimodal-assisted odometry,
PR(153), 2024, pp. 110573.
Elsevier DOI
2405
Visual odometry, Pose estimation, Visual reconstruction,
Multimodal assisted, Triple-modal fusion, Image-based mask
BibRef
Wang, Z.[Zhong],
Zhang, L.[Lin],
Zhao, S.J.[Sheng-Jie],
Zhou, Y.C.[Yi-Cong],
Ct-LVI: A Framework Toward Continuous-Time Laser-Visual-Inertial
Odometry and Mapping,
CirSysVideo(34), No. 6, June 2024, pp. 4378-4391.
IEEE DOI Code:
HTML Version.
2406
Visualization, Simultaneous localization and mapping, Odometry,
Feature extraction, Trajectory, Sensors, Cameras,
data fusion
BibRef
Wu, Y.Z.[Yu-Zhen],
Wang, L.X.[Ling-Xue],
Zhang, L.[Lian],
Han, X.D.[Xu-Dong],
Zheng, D.[Dezhi],
Wang, S.[Shuigen],
Li, Y.Q.[Yan-Qiu],
Cai, Y.[Yi],
Catadioptric omnidirectional thermal odometry in dynamic environment,
PandRS(216), 2024, pp. 45-65.
Elsevier DOI
2408
Thermal odometry, Catadioptric omnidirectional camera,
Camera calibration, Dynamic environment, Pose estimation, Mobile mapping
BibRef
Ott, F.[Felix],
Heublein, L.[Lucas],
Rügamer, D.[David],
Bischl, B.[Bernd],
Mutschler, C.[Christopher],
Fusing structure from motion and simulation-augmented pose regression
from optical flow for challenging indoor environments,
JVCIR(103), 2024, pp. 104256.
Elsevier DOI
2409
Visual self-localization, Structure from motion, Pose regression,
Optical flow, Pose graph optimization, Challenging environment
BibRef
Ott, F.,
Feigl, T.,
Löffler, C.,
Mutschler, C.,
ViPR: Visual-Odometry-aided Pose Regression for 6DoF Camera
Localization,
VisualSLAM20(187-198)
IEEE DOI
2008
Cameras, Task analysis, Pose estimation, Feature extraction,
Navigation, Optical imaging, Sensors
BibRef
Xu, W.T.[Wan-Ting],
Zhang, S.[Si'Ao],
Cui, L.[Li],
Peng, X.[Xin],
Kneip, L.[Laurent],
Event-Based Visual Odometry on Non-Holonomic Ground Vehicles,
3DV24(831-841)
IEEE DOI Code:
WWW Link.
2408
Tracking, Lighting, Sensor fusion, Feature extraction,
Taylor series, Land vehicles
BibRef
Lee, C.N.[Cheng-Nan],
Schofield, S.[Sam],
Green, R.[Richard],
Bainbridge-Smith, A.[Andrew],
Automatic Exposure and Pose Estimation Error,
IVCNZ23(1-6)
IEEE DOI
2403
Measurement, Image quality, Correlation, Heuristic algorithms,
Pose estimation, Brightness, Trajectory, visual odometry,
pose estimation error
BibRef
Chiu, C.C.[Chu-Chi],
Yang, H.K.[Hsuan-Kung],
Chen, H.W.[Hao-Wei],
Chen, Y.W.[Yu-Wen],
Lee, C.Y.[Chun-Yi],
ViTVO: Vision Transformer based Visual Odometry with Attention
Supervision,
MVA23(1-5)
DOI Link
2403
Training, Degradation, Machine vision, Semantics, Dynamics,
Transformers, Noise measurement
BibRef
Lai, L.[Lei],
Shangguan, Z.K.[Zhong-Kai],
Zhang, J.[Jimuyang],
Ohn-Bar, E.[Eshed],
XVO: Generalized Visual Odometry via Cross-Modal Self-Training,
ICCV23(10060-10071)
IEEE DOI
2401
BibRef
Kuznietsov, Y.[Yevhen],
Proesmans, M.[Marc],
Van Gool, L.J.[Luc J.],
Replay-based Online Adaptation for Unsupervised Deep Visual Odometry,
CIARP23(I:674-684).
Springer DOI
2312
BibRef
Huang, L.Y.[Li-Yang],
Huang, S.S.[Shao-Syuan],
Chien, S.Y.[Shao-Yi],
DPDM: Feature-Based Pose Refinement with Deep Pose and Deep Match for
Monocular Visual Odometry,
ICIP23(1370-1374)
IEEE DOI
2312
BibRef
Abreu, S.[Steven],
Gouda, M.[Muhammed],
Lugnan, A.[Alessio],
Bienstman, P.[Peter],
Flow cytometry with event-based vision and spiking neuromorphic
hardware,
EventVision23(4139-4147)
IEEE DOI
2309
BibRef
Kosta, A.K.[Adarsh Kumar],
Apolinario, M.P.E.[Marco Paul E.],
Roy, K.[Kaushik],
Live Demonstration: ANN vs SNN vs Hybrid Architectures for
Event-based Real-time Gesture Recognition and Optical Flow Estimation,
EventVision23(4148-4149)
IEEE DOI
2309
BibRef
Ye, W.[Weicai],
Lan, X.Y.[Xin-Yue],
Chen, S.[Shuo],
Ming, Y.H.[Yu-Hang],
Yu, X.Y.[Xing-Yuan],
Bao, H.J.[Hu-Jun],
Cui, Z.P.[Zhao-Peng],
Zhang, G.F.[Guo-Feng],
PVO: Panoptic Visual Odometry,
CVPR23(9579-9589)
IEEE DOI
2309
BibRef
Memmel, M.[Marius],
Bachmann, R.[Roman],
Zamir, A.[Amir],
Modality-invariant Visual Odometry for Embodied Vision,
CVPR23(21549-21559)
IEEE DOI
2309
BibRef
Vödisch, N.[Niclas],
Cattaneo, D.[Daniele],
Burgard, W.[Wolfram],
Valada, A.[Abhinav],
CoVIO: Online Continual Learning for Visual-Inertial Odometry,
CLVision23(2464-2473)
IEEE DOI
2309
BibRef
Nemcovsky, Y.[Yaniv],
Jacoby, M.[Matan],
Bronstein, A.M.[Alex M.],
Baskin, C.[Chaim],
Physical Passive Patch Adversarial Attacks on Visual Odometry Systems,
ACCV22(VII:518-534).
Springer DOI
2307
BibRef
Chen, H.W.[Hao-Wei],
Liao, T.H.[Ting-Hsuan],
Yang, H.K.[Hsuan-Kung],
Lee, C.Y.[Chun-Yi],
Pixel-Wise Prediction based Visual Odometry via Uncertainty
Estimation,
WACV23(2517-2527)
IEEE DOI
2302
Training, Visualization, Uncertainty, Training data, Estimation,
Noise measurement, Task analysis, Visual odometry,
pixel-wised predictions
BibRef
Hariat, M.[Marwane],
Manzanera, A.[Antoine],
Filliat, D.[David],
Rebalancing gradient to improve self-supervised co-training of depth,
odometry and optical flow predictions,
WACV23(1267-1276)
IEEE DOI
2302
Training, Optical losses, Visualization, Adaptation models, Codes, Estimation
BibRef
Huang, J.[Ji],
Zhang, Y.[Yanduo],
Li, X.[Xun],
Lidar-Visual-Inertial Odometry Using Point and Line Features,
ICRVC22(215-222)
IEEE DOI
2301
Visualization, Laser radar, Computational modeling,
Pose estimation, Robot vision systems, Feature extraction,
virtual stereo camera model
BibRef
Zhan, J.R.[Jia-Rong],
Lin, H.Y.[Huei-Yung],
Improving Visual Inertial Odometry with UWB Positioning for UAV
Indoor Navigation,
ICPR22(4189-4195)
IEEE DOI
2212
Vibrations, Performance evaluation, Location awareness,
Visualization, Simultaneous localization and mapping, Robustness
BibRef
Yang, M.Y.[Ming-Yu],
Chen, Y.[Yu],
Kim, H.S.[Hun-Seok],
Efficient Deep Visual and Inertial Odometry with Adaptive Visual
Modality Selection,
ECCV22(XXXVIII:233-250).
Springer DOI
2211
BibRef
Kloukiniotis, A.[Andreas],
Papandreou, A.[Andreas],
Anagnostopoulos, C.[Christos],
Lalos, A.[Aris],
Kapsalas, P.[Petros],
Nguyen, D.V.,
Moustakas, K.[Konstantinos],
CarlaScenes: A synthetic dataset for odometry in autonomous driving,
WAD22(4519-4527)
IEEE DOI
2210
Deep learning, Laser radar, Semantics, XML, Trajectory
BibRef
Cao, X.[Xiya],
Zhou, C.[Caifa],
Zeng, D.D.[Dan-Dan],
Wang, Y.L.[Yong-Liang],
RIO: Rotation-equivariance supervised learning of robust inertial
odometry,
CVPR22(6604-6613)
IEEE DOI
2210
Training, Adaptation models, Uncertainty, Codes,
Computational modeling, Supervised learning, Motion and tracking,
Efficient learning and inferences
BibRef
Hidalgo-Carrió, J.[Javier],
Gallego, G.[Guillermo],
Scaramuzza, D.[Davide],
Event-aided Direct Sparse Odometry,
CVPR22(5771-5780)
IEEE DOI
2210
Code, Odometry.
WWW Link. Bundle adjustment, Tracking loops, Technological innovation,
Sensitivity, Codes, Target tracking, Brightness, Low-level vision,
Robot vision
BibRef
Zhao, X.M.[Xiao-Ming],
Agrawal, H.[Harsh],
Batra, D.[Dhruv],
Schwing, A.[Alexander],
The Surprising Effectiveness of Visual Odometry Techniques for
Embodied PointGoal Navigation,
ICCV21(16107-16116)
IEEE DOI
2203
Location awareness, Visualization, Navigation, Sensors, Reliability,
Noise measurement, Task analysis,
BibRef
Liu, P.[Peidong],
Zuo, X.X.[Xing-Xing],
Larsson, V.[Viktor],
Pollefeys, M.[Marc],
MBA-VO: Motion Blur Aware Visual Odometry,
ICCV21(5530-5539)
IEEE DOI
2203
Codes, Pipelines, Benchmark testing, Cameras, Robustness, Trajectory,
Visual odometry, Stereo, 3D from multiview and other sensors,
Vision applications and systems
BibRef
Seiskari, O.[Otto],
Rantalankila, P.[Pekka],
Kannala, J.H.[Ju-Ho],
Ylilammi, J.[Jerry],
Rahtu, E.[Esa],
Solin, A.[Arno],
HybVIO: Pushing the Limits of Real-time Visual-inertial Odometry,
WACV22(287-296)
IEEE DOI
2202
Simultaneous localization and mapping,
Benchmark testing, Feature extraction, Real-time systems, Hardware,
Vision for Aerial/Drone/Underwater/Ground Vehicles
BibRef
Schofield, S.[Sam],
Bainbridge-Smith, A.[Andrew],
Green, R.[Richard],
Evaluating Visual Inertial Odometry Using the Windy Forest Dataset,
IVCNZ21(1-6)
IEEE DOI
2201
BibRef
Xu, S.[Sangni],
Xiong, H.[Hao],
Wu, Q.X.[Qiu-Xia],
Wang, Z.Y.[Zhi-Yong],
Attention-based Long-term Modeling for Deep Visual Odometry,
DICTA21(1-8)
IEEE DOI
2201
Visualization, Computational modeling, Robot vision systems,
Logic gates, Feature extraction, Cameras, Image sequences, LSTM
BibRef
Andrei, S.S.[Silviu S.],
Agam, G.[Gady],
Unsupervised Learning of Visual Odometry Using Direct Motion Modeling,
ICIP21(3662-3666)
IEEE DOI
2201
Visualization, Image processing, Supervised learning,
Pose estimation, Predictive models, Unsupervised learning,
deep learning
BibRef
Liu, D.[Daqi],
Parra, Á.[Álvaro],
Chin, T.J.[Tat-Jun],
Spatiotemporal Registration for Event-based Visual Odometry,
CVPR21(4935-4944)
IEEE DOI
2111
Tracking loops, Image resolution, Tracking, Motion estimation,
Pipelines, Robot sensing systems, Spatiotemporal phenomena
BibRef
Kahmen, O.,
Haase, N.,
Luhmann, T.,
Orientation of Point Clouds for Complex Surfaces In Medical Surgery
Using Trinocular Visual Odometry and Stereo Orb-SLAM2,
ISPRS20(B2:35-42).
DOI Link
2012
BibRef
Wan, Y.,
Gao, W.,
Han, S.,
Wu, Y.,
Dynamic Object-Aware Monocular Visual Odometry With Local And Global
Information Aggregation,
ICIP20(603-607)
IEEE DOI
2011
Feature extraction, Optical imaging, Cameras,
Optical variables control, Training, Visual odometry,
Deep learning
BibRef
Zou, Y.L.[Yu-Liang],
Ji, P.[Pan],
Tran, Q.H.[Quoc-Huy],
Huang, J.B.[Jia-Bin],
Chandraker, M.[Manmohan],
Learning Monocular Visual Odometry via Self-supervised Long-term
Modeling,
ECCV20(XIV:710-727).
Springer DOI
2011
BibRef
Yang, N.,
von Stumberg, L.,
Wang, R.,
Cremers, D.,
D3VO: Deep Depth, Deep Pose and Deep Uncertainty for Monocular Visual
Odometry,
CVPR20(1278-1289)
IEEE DOI
2008
Uncertainty, Estimation, Brightness, Training, Cameras,
Neural networks, Lighting
BibRef
Huang, J.,
Yang, S.,
Mu, T.,
Hu, S.,
ClusterVO: Clustering Moving Instances and Estimating Visual Odometry
for Self and Surroundings,
CVPR20(2165-2174)
IEEE DOI
2008
Feature extraction, Simultaneous localization and mapping,
Semantics, Tracking, Dynamics
BibRef
Min, Z.,
Yang, Y.,
Dunn, E.,
VOLDOR: Visual Odometry From Log-Logistic Dense Optical Flow
Residuals,
CVPR20(4897-4908)
IEEE DOI
2008
Adaptive optics, Optical variables control, Cameras,
Optical imaging, Optical sensors, Optical computing, Estimation
BibRef
Fontán, A.,
Civera, J.,
Triebel, R.,
Information-Driven Direct RGB-D Odometry,
CVPR20(4928-4936)
IEEE DOI
2008
Simultaneous localization and mapping, Cameras,
Jacobian matrices, Optimization, Entropy, Visual odometry, Covariance matrices
BibRef
Kuo, X.,
Liu, C.,
Lin, K.,
Lee, C.,
Dynamic Attention-based Visual Odometry,
VisualSLAM20(160-169)
IEEE DOI
2008
Semantics, Cameras, Trajectory, Pose estimation, Visual odometry, Dynamics
BibRef
Nabavi, S.S.,
Hosseinzadeh, M.,
Fahimi, R.,
Wang, Y.,
Unsupervised Learning of Camera Pose with Compositional Re-estimation,
WACV20(11-20)
IEEE DOI
2006
Cameras, Pose estimation, Video sequences, Visual odometry,
Image reconstruction, Unsupervised learning
BibRef
Cheng, R.,
Agia, C.,
Meger, D.,
Dudek, G.,
Depth Prediction for Monocular Direct Visual Odometry,
CRV20(70-77)
IEEE DOI
2006
depth prediction, visual odometry, deep learning, visual SLAM
BibRef
Saputra, M.R.U.[Muhamad Risqi U.],
Gusmao, P.[Pedro],
Almalioglu, Y.[Yasin],
Markham, A.[Andrew],
Trigoni, N.[Niki],
Distilling Knowledge From a Deep Pose Regressor Network,
ICCV19(263-272)
IEEE DOI
2004
distance measurement, knowledge management, Uncertainty,
learning (artificial intelligence), neural nets, pose estimation.
BibRef
Rukhovich, D.,
Mouritzen, D.,
Kaestner, R.,
Rufli, M.,
Velizhev, A.,
Estimation of Absolute Scale in Monocular SLAM Using Synthetic Data,
CVRSUAD19(803-812)
IEEE DOI
2004
cameras, feature extraction, neural nets,
SLAM (robots), unsupervised learning, monocular SLAM, Visual odometry
BibRef
Xue, F.[Fei],
Wang, X.[Xin],
Li, S.[Shunkai],
Wang, Q.Y.[Qiu-Yuan],
Wang, J.Q.[Jun-Qiu],
Zha, H.B.[Hong-Bin],
Beyond Tracking: Selecting Memory and Refining Poses for Deep Visual
Odometry,
CVPR19(8567-8575).
IEEE DOI
2002
BibRef
Chen, C.H.[Chang-Hao],
Rosa, S.[Stefano],
Miao, Y.[Yishu],
Lu, C.X.X.[Chris Xiao-Xuan],
Wu, W.[Wei],
Markham, A.[Andrew],
Trigoni, N.[Niki],
Selective Sensor Fusion for Neural Visual-Inertial Odometry,
CVPR19(10534-10543).
IEEE DOI
2002
BibRef
Wang, R.[Rui],
Pizer, S.M.[Stephen M.],
Frahm, J.M.[Jan-Michael],
Recurrent Neural Network for (Un-)Supervised Learning of Monocular
Video Visual Odometry and Depth,
CVPR19(5550-5559).
IEEE DOI
2002
BibRef
Dai, W.,
Zhang, Y.,
Sun, D.,
Hovakimyan, N.,
Li, P.,
Multi-Spectral Visual Odometry without Explicit Stereo Matching,
3DV19(443-452)
IEEE DOI
1911
Cameras, Visual odometry, Measurement, Standards, Lighting,
Optimization, Egomotion estimation,
Multi spectral sensors
BibRef
Singh, G.,
Wu, M.,
Lam, S.,
Revisiting Visual Odometry for Real-Time Performance,
MVA19(1-6)
DOI Link
1806
driver information systems, mobile robots, object detection,
object tracking, optimisation, pose estimation, robot vision,
Simultaneous localization and mapping
BibRef
Irmisch, P.,
Baumbach, D.,
Ernst, I.,
Börner, A.,
Simulation Framework for a Visual-Inertial Navigation System,
ICIP19(1995-1999)
IEEE DOI
1910
Visual-inertial odometry, simulation framework, motion profile,
rendering, motion blur
BibRef
Liu, H.,
Ma, H.,
Zhang, L.,
Visual Odometry based on Semantic Supervision,
ICIP19(2566-2570)
IEEE DOI
1910
Visual odometry, feature selection, semantic understanding, attention region
BibRef
Lu, Y.,
Lu, G.,
Deep Unsupervised Learning for Simultaneous Visual Odometry and Depth
Estimation,
ICIP19(2571-2575)
IEEE DOI
1910
Visual odometry, Depth estimation, Convolutional neural network
BibRef
Hou, Z.X.[Zhi-Xing],
Ding, Y.Q.[Ya-Qing],
Wang, Y.[Ying],
Yang, H.[Hang],
Kong, H.[Hui],
Visual Odometry for Indoor Mobile Robot by Recognizing Local Manhattan
Structures,
ACCV18(V:168-182).
Springer DOI
1906
BibRef
Xue, F.[Fei],
Wang, Q.Y.[Qiu-Yuan],
Wang, X.[Xin],
Dong, W.[Wei],
Wang, J.Q.[Jun-Qiu],
Zha, H.B.[Hong-Bin],
Guided Feature Selection for Deep Visual Odometry,
ACCV18(VI:293-308).
Springer DOI
1906
BibRef
Wang, X.[Xin],
Xue, F.[Fei],
Yan, Z.[Zike],
Dong, W.[Wei],
Wang, Q.Y.[Qiu-Yuan],
Zha, H.B.[Hong-Bin],
Continuous-Time Stereo Visual Odometry Based on Dynamics Model,
ACCV18(VI:388-403).
Springer DOI
1906
BibRef
Rodriguez-Peral, C.M.[Carlos Marquez],
Peña, D.[Dexmont],
Analysis of the Effect of Sensors for End-to-End Machine Learning
Odometry,
ACVR18(VI:82-95).
Springer DOI
1905
BibRef
Ganoni, O.,
Mukundan, R.,
Green, R.,
A multi sensory approach using error bounds for improved visual
odometry,
IVCNZ17(1-6)
IEEE DOI
1902
accelerometers, cameras, distance measurement, pressure sensors,
robot vision, multisensory approach, error bounds,
Computer simulation
BibRef
Iyer, G.,
Murthy, J.K.,
Gupta, G.,
Krishna, K.M.,
Paull, L.,
Geometric Consistency for Self-Supervised End-to-End Visual Odometry,
DeepSLAM18(380-3808)
IEEE DOI
1812
Training, Cameras, Task analysis, Estimation, Transforms,
Visualization, Trajectory
BibRef
Mahé, H.,
Marraud, D.,
Comport, A.I.,
Semantic-only Visual Odometry based on dense class-level segmentation,
ICPR18(1989-1995)
IEEE DOI
1812
Semantics, Cameras, Visual odometry, Tracking, Estimation,
Feature extraction, Minimization
BibRef
Jin, J.,
Zhu, X.,
Jiang, Y.,
Du, Z.,
Localization Based on Semantic Map and Visual Inertial Odometry,
ICPR18(2410-2415)
IEEE DOI
1812
Semantics, Cameras,
Visualization, Optimization, Autonomous vehicles
BibRef
Wu, X.,
Pradalier, C.,
Multi-scale Direct Sparse Visual Odometry for Large-Scale Natural
Environment,
3DV18(89-97)
IEEE DOI
1812
cameras, distance measurement, image reconstruction,
motion estimation, multiscale direct sparse visual odometry,
Large-Scale Reconstruction
BibRef
Zhan, H.Y.[Huang-Ying],
Garg, R.[Ravi],
Weerasekera, C.S.[Chamara Saroj],
Li, K.[Kejie],
Agarwal, H.[Harsh],
Reid, I.D.[Ian D.],
Unsupervised Learning of Monocular Depth Estimation and Visual
Odometry with Deep Feature Reconstruction,
CVPR18(340-349)
IEEE DOI
1812
Estimation, Cameras, Visual odometry, Training, Task analysis,
Image reconstruction
BibRef
Wang, C.,
Buenaposada, J.M.,
Zhu, R.,
Lucey, S.,
Learning Depth from Monocular Videos Using Direct Methods,
CVPR18(2022-2030)
IEEE DOI
1812
Training, Videos, Cameras, Estimation, Visual odometry,
Pipelines, Loss measurement
BibRef
Swedish, T.,
Raskar, R.,
Deep Visual Teach and Repeat on Path Networks,
Odometry18(1614-161409)
IEEE DOI
1812
Visualization, Image sequences, Navigation, Visual odometry,
Cameras, Simultaneous localization and mapping
BibRef
Manderson, T.,
Holliday, A.,
Dudek, G.,
Gaze Selection for Enhanced Visual Odometry During Navigation,
CRV18(110-117)
IEEE DOI
1812
Cameras, Simultaneous localization and mapping, Visual odometry,
Visualization, Real-time systems, Motion estimation,
SLAM
BibRef
Lianos, K.N.[Konstantinos-Nektarios],
Schönberger, J.L.[Johannes L.],
Pollefeys, M.[Marc],
Sattler, T.[Torsten],
VSO: Visual Semantic Odometry,
ECCV18(II: 246-263).
Springer DOI
1810
BibRef
Cortés, S.[Santiago],
Solin, A.[Arno],
Rahtu, E.[Esa],
Kannala, J.H.[Ju-Ho],
ADVIO: An Authentic Dataset for Visual-Inertial Odometry,
ECCV18(X: 425-440).
Springer DOI
1810
BibRef
Ling, Y.G.[Yong-Gen],
Bao, L.C.[Lin-Chao],
Jie, Z.Q.[Ze-Qun],
Zhu, F.M.[Feng-Ming],
Li, Z.Y.[Zi-Yang],
Tang, S.M.[Shan-Min],
Liu, Y.S.[Yong-Sheng],
Liu, W.[Wei],
Zhang, T.[Tong],
Modeling Varying Camera-IMU Time Offset in Optimization-Based
Visual-Inertial Odometry,
ECCV18(IX: 491-507).
Springer DOI
1810
BibRef
Pan, L.,
Cheng, J.,
Zhang, Q.,
UFSM VO: Stereo Odometry Based on Uniformly Feature Selection and
Strictly Correspondence Matching,
ICIP18(4148-4152)
IEEE DOI
1809
Feature extraction, Cameras, Estimation, Visualization, Robustness,
Robot vision systems, Simultaneous localization and mapping,
pose estimation
BibRef
Fanani, N.,
Mester, R.,
The precision of triangulation in monocular visual odometry,
Southwest18(1-4)
IEEE DOI
1809
Cameras,
Sensitivity, Meters, Visual odometry, Geometry
BibRef
Wang, X.[Xin],
Dong, W.[Wei],
Zhou, M.C.[Ming-Cai],
Li, R.[Renju],
Zha, H.B.[Hong-Bin],
Edge Enhanced Direct Visual Odometry,
BMVC16(xx-yy).
HTML Version.
1805
BibRef
Lee, J.K.[Jeong-Kyun],
Yoon, K.J.[Kuk-Jin],
Three-Point Direct Stereo Visual Odometry,
BMVC16(xx-yy).
HTML Version.
1805
BibRef
MacTavish, K.,
Paton, M.,
Barfoot, T.D.,
Night Rider: Visual Odometry Using Headlights,
CRV17(314-320)
IEEE DOI
1804
cameras, distance measurement, image sensors, light sources,
mobile robots, motion estimation, robot vision,
visual odometry
BibRef
Pereira, F.,
Luft, J.,
Ilha, G.,
Sofiatti, A.,
Susin, A.,
Backward Motion for Estimation Enhancement in Sparse Visual Odometry,
WVC17(61-66)
IEEE DOI
1804
cameras, distance measurement, mobile robots, motion estimation,
pose estimation, robot vision, stereo image processing,
Visual Odometry
BibRef
da Silva, B.M.F.[Bruno Marques F.],
Maciel Correia, L.F.[Luiz Felipe],
de Araujo Bezerra, K.[Kallil],
Garcia Gonsalves, L.M.[Luiz Marcos],
Tracking Spatially Distributed Features in KLT Algorithms for RGB-D
Visual Odometry,
WVC17(67-72)
IEEE DOI
1804
feature extraction, image sensors, mobile robots,
motion estimation, object tracking, robot vision,
Visual odometry
BibRef
Fu, Z.,
Quo, Y.,
Lin, Z.,
An, W.,
FSVO: Semi-direct monocular visual odometry using fixed maps,
ICIP17(2553-2557)
IEEE DOI
1803
Cameras, Feature extraction, Minimization, Motion estimation,
Robustness, Visual odometry, Fixed-Map,
Visual Odometry
BibRef
Chien, H.J.[Hsiang-Jen],
Lin, J.J.[Jr-Jiun],
Yin, T.K.[Tang-Kai],
Klette, R.[Reinhard],
Multi-objective Visual Odometry,
PSIVT17(62-74).
Springer DOI
1802
BibRef
Wang, R.,
Schwörer, M.,
Cremers, D.,
Stereo DSO: Large-Scale Direct Sparse Visual Odometry with Stereo
Cameras,
ICCV17(3923-3931)
IEEE DOI
1802
distance measurement, image reconstruction, image sequences,
optimisation, stereo image processing, 3D reconstruction,
BibRef
Bose, L.,
Chen, J.,
Carey, S.J.,
Dudek, P.,
Mayol-Cuevas, W.W.,
Visual Odometry for Pixel Processor Arrays,
ICCV17(4614-4622)
IEEE DOI
1802
Cameras, Registers, Sensor arrays, Shearing, Visualization
BibRef
Wang, Y.[Yifu],
Kneip, L.[Laurent],
On Scale Initialization in Non-overlapping Multi-perspective Visual
Odometry,
CVS17(144-157).
Springer DOI
1711
BibRef
Zhu, A.Z.[Alex Zihao],
Atanasov, N.,
Daniilidis, K.[Kostas],
Event-Based Visual Inertial Odometry,
CVPR17(5816-5824)
IEEE DOI
1711
Adaptive optics, Cameras, Optical imaging, Optical sensors,
Spatiotemporal phenomena, Tracking
BibRef
Wong, X.I.,
Majji, M.,
Uncertainty Quantification of Lucas Kanade Feature Track and
Application to Visual Odometry,
Odometry17(950-958)
IEEE DOI
1709
Algorithm design and analysis, Computational modeling,
Covariance matrices, Feature extraction, Uncertainty, Visualization
BibRef
Maier, J.,
Humenberger, M.,
Zendel, O.,
Vincze, M.,
Ground Truth Accuracy and Performance of the Matching Pipeline,
Odometry17(969-979)
IEEE DOI
1709
Benchmark testing, Detectors, Feature extraction,
Pipelines, Runtime
BibRef
Martinez, G.,
Field tests on flat ground of an intensity-difference based monocular
visual odometry algorithm for planetary rovers,
MVA17(161-164)
DOI Link
1708
Cameras, Extraterrestrial measurements, Robot vision systems,
Shape, Visualization
BibRef
Muller, P.,
Savakis, A.E.[Andreas E.],
Flowdometry: An Optical Flow and Deep Learning Based Approach to
Visual Odometry,
WACV17(624-631)
IEEE DOI
1609
Adaptive optics, Cameras, Computer architecture, Optical imaging,
Optical network units, Video sequences, Visualization
BibRef
Chien, H.J.[Hsiang-Jen],
Klette, R.,
Schneider, N.,
Franke, U.,
Visual odometry driven online calibration for monocular LiDAR-camera
systems,
ICPR16(2848-2853)
IEEE DOI
1705
Calibration, Cameras, Estimation, Image edge detection, Laser radar,
Visualization
BibRef
Zhang, Y.G.[Yi-Gong],
Hou, Z.X.[Zhi-Xing],
Yang, J.[Jian],
Kong, H.[Hui],
Maximum clique based RGB-D visual odometry,
ICPR16(2764-2769)
IEEE DOI
1705
Cameras, Estimation, Feature extraction, Motion segmentation,
Visualization, RGB-D camera, feature point, line segment,
maximum clique, visual, odometry
BibRef
Resch, B.[Benjamin],
Wei, J.[Jian],
Lensch, H.P.A.[Hendrik P. A.],
Real Time Direct Visual Odometry for Flexible Multi-camera Rigs,
ACCV16(IV: 503-518).
Springer DOI
1704
BibRef
Zhang, H.,
Ernst, I.,
Zuev, S.,
Börner, A.,
Knoche, M.,
Klette, R.,
Visual Odometry and 3D Point Clouds Under Low-Light Conditions,
IVCNZ18(1-6)
IEEE DOI
1902
Trajectory, IP networks, Cameras,
Feature extraction, Visual odometry, Roads
BibRef
Chien, H.J.,
Klette, R.,
Substantial improvement of stereo visual odometry by multi-path
feature tracking,
IVCNZ17(1-6)
IEEE DOI
1902
cameras, distance measurement, feature extraction, image sequences,
motion estimation, robot vision, stereo image processing, tracking,
Visual odometry
BibRef
Chien, H.J.,
Chuang, C.C.,
Chen, C.Y.,
Klette, R.,
When to use what feature? SIFT, SURF, ORB, or A-KAZE features for
monocular visual odometry,
ICVNZ16(1-6)
IEEE DOI
1701
Cameras
BibRef
Xu, W.J.[Wen-Ju],
Choi, D.[Dongkyu],
Direct Visual-Inertial Odometry and Mapping for Unmanned Vehicle,
ISVC16(II: 595-604).
Springer DOI
1701
BibRef
de Mattos Nascimento, M.[Marcelo],
Fernandez, M.E.L.[Manuel Eduardo Loaiza],
Raposo, A.B.[Alberto Barbosa],
Using Dense 3D Reconstruction for Visual Odometry Based on Structure
from Motion Techniques,
ISVC16(II: 483-493).
Springer DOI
1701
BibRef
Deigmoeller, J.[Joerg],
Eggert, J.[Julian],
Stereo Visual Odometry Without Temporal Filtering,
GCPR16(166-175).
Springer DOI
1611
BibRef
Dong, X.S.[Xing-Shuai],
Dong, X.H.[Xing-Hui],
Dong, J.Y.[Jun-Yu],
Monocular Visual-IMU Odometry: A Comparative Evaluation of the
Detector-Descriptor Based Methods,
CVRoads16(I: 81-95).
Springer DOI
1611
BibRef
Kersten, J.,
Rodehorst, V.,
Enhancement Strategies For Frame-to-frame Uas Stereo Visual Odometry,
ISPRS16(B3: 511-518).
DOI Link
1610
BibRef
Tarrio, J.J.,
Pedre, S.,
Realtime Edge-Based Visual Odometry for a Monocular Camera,
ICCV15(702-710)
IEEE DOI
1602
Cameras
BibRef
Lu, Y.,
Song, D.,
Robust RGB-D Odometry Using Point and Line Features,
ICCV15(3934-3942)
IEEE DOI
1602
Cameras
BibRef
Chien, H.J.[Hsiang-Jen],
Geng, H.[Haokun],
Chen, C.Y.[Chia-Yen],
Klette, R.[Reinhard],
Multi-frame Feature Integration for Multi-camera Visual Odometry,
PSIVT15(27-37).
Springer DOI
1602
BibRef
Mirabdollah, M.H.[M. Hossein],
Mertsching, B.[Bärbel],
Fast Techniques for Monocular Visual Odometry,
GCPR15(297-307).
Springer DOI
1511
BibRef
Alletto, S.[Stefano],
Serra, G.[Giuseppe],
Cucchiara, R.[Rita],
Egocentric Object Tracking: An Odometry-Based Solution,
CIAP15(II:687-696).
Springer DOI
1511
BibRef
Fularz, M.[Michal],
Nowicki, M.[Michal],
Skrzypczynski, P.[Piotr],
Adopting Feature-Based Visual Odometry for Resource-Constrained Mobile
Devices,
ICIAR14(II: 431-441).
Springer DOI
1410
BibRef
Wadenback, M.[Marten],
Heyden, A.[Anders],
Trajectory Estimation Using Relative Distances Extracted from
Inter-image Homographies,
CRV14(232-237)
IEEE DOI
1406
Cameras
BibRef
Peretroukhin, V.[Valentin],
Kelly, J.[Jonathan],
Barfoot, T.D.[Timothy D.],
Optimizing Camera Perspective for Stereo Visual Odometry,
CRV14(1-7)
IEEE DOI
1406
Cameras
BibRef
Farboud-Sheshdeh, S.[Sara],
Barfoot, T.D.[Timothy D.],
Kwong, R.H.[Raymond H.],
Towards Estimating Bias in Stereo Visual Odometry,
CRV14(8-15)
IEEE DOI
1406
Cameras
BibRef
Badino, H.,
Yamamoto, A.,
Kanade, T.,
Visual Odometry by Multi-frame Feature Integration,
AutoDrive13(222-229)
IEEE DOI
1403
cameras
BibRef
Zienkiewicz, J.[Jacek],
Lukierski, R.[Robert],
Davison, A.[Andrew],
Dense, Auto-Calibrating Visual Odometry from a Downward-Looking Camera,
BMVC13(xx-yy).
DOI Link
1402
BibRef
Straub, J.,
Hilsenbeck, S.,
Schroth, G.,
Huitl, R.,
Moller, A.,
Steinbach, E.,
Fast relocalization for visual odometry using binary features,
ICIP13(2548-2552)
IEEE DOI
1402
BRIEF;Locality Sensitive Hashing;ORB;Relocalization;Visual Odometry
BibRef
Martinez, G.,
Monocular visual odometry from frame to frame intensity differences
for planetary exploration mobile robots,
WORV13(54-59)
IEEE DOI
1307
aerospace robotics
BibRef
Jeong, J.[Jaeheon],
Mulligan, J.[Jane],
Correll, N.[Nikolaus],
Trinocular visual odometry for divergent views with minimal overlap,
WORV13(229-236)
IEEE DOI
1307
BibRef
Boulekchour, M.[Mohammed],
Aouf, N.[Nabil],
L_inf Norm Based Solution for Visual Odometry,
CAIP13(II:185-192).
Springer DOI
1311
BibRef
Diamantas, S.C.[Sotirios Ch.],
Dasgupta, P.[Prithviraj],
An Active Vision Approach to Height Estimation with Optical Flow,
ISVC13(I:160-170).
Springer DOI
1310
BibRef
Hadsell, R.[Raia],
Matei, B.[Bogdan],
Salgian, G.[Garbis],
Das, A.[Aveek],
Oskiper, T.[Taragay],
Samarasekera, S.[Supun],
Complex Terrain Mapping with Multi-camera Visual Odometry and Realtime
Drift Correction,
3DIMPVT12(493-500).
IEEE DOI
1212
BibRef
Musleh, B.[Basam],
Martin, D.[David],
de la Escalera, A.[Arturo],
Guinea, D.M.[Domingo Miguel],
Garcia-Alegre, M.C.[Maria Carmen],
Estimation and Prediction of the Vehicle's Motion Based on Visual
Odometry and Kalman Filter,
ACIVS12(491-502).
Springer DOI
1209
BibRef
van Hamme, D.[David],
Veelaert, P.[Peter],
Philips, W.[Wilfried],
Robust Visual Odometry Using Uncertainty Models,
ACIVS11(1-12).
Springer DOI
1108
BibRef
Goldberg, S.B.[Steven B.],
Matthies, L.H.[Larry H.],
Stereo and IMU assisted visual odometry on an OMAP3530 for small robots,
ECVW11(169-176).
IEEE DOI
1106
See also Stereo Vision for Planetary Rovers: Stochastic Modeling to Near Real-Time Implementation.
BibRef
Israel, J.[Jonathan],
Plyer, A.[Aurelien],
A brute force approach to depth camera odometry,
ConDepth11(1141-1146).
IEEE DOI
1201
BibRef
Tykkala, T.[Tommi],
Audras, C.[Cedric],
Comport, A.I.[Andrew I.],
Direct Iterative Closest Point for real-time visual odometry,
CVVT11(2050-2056).
IEEE DOI
1201
BibRef
Eudes, A.[Alexandre],
Lhuillier, M.[Maxime],
Naudet-Collette, S.[Sylvie],
Dhome, M.[Michel],
Fast Odometry Integration in Local Bundle Adjustment-Based Visual SLAM,
ICPR10(290-293).
IEEE DOI
1008
BibRef
And: A1, A3, A2, A4:
Weighted Local Bundle Adjustment and Application to Odometry and Visual
SLAM Fusion,
BMVC10(xx-yy).
HTML Version.
1009
BibRef
Jiang, R.[Ruyi],
Klette, R.[Reinhard],
Wang, S.G.[Shi-Gang],
Statistical Modeling of Long-Range Drift in Visual Odometry,
CVVT10(214-224).
Springer DOI
1109
BibRef
And:
Modeling of Unbounded Long-Range Drift in Visual Odometry,
PSIVT10(121-126).
IEEE DOI
1011
BibRef
Hansen, P.[Peter],
Alismail, H.S.[Hatem Said],
Rander, P.[Peter], and
Browning, B.[Brett],
Towards a Visual Perception System for Pipe Inspection:
Monocular Visual Odometry,
CMU-RI-TR-10-22, July, 2010.
WWW Link.
1102
networks of pipes.
BibRef
Huang, Y.W.[Yun-Wen],
Chiang, K.W.[Kai-Wei],
Improving the performance of MEMS IMU/GPS POS systems for land based
MMS utilizing tightly coupled integration and odometer,
CGC10(131).
PDF File.
1006
BibRef
Dubbelman, G.[Gijs],
Groen, F.C.A.[Frans C.A.],
Bias reduction for stereo based motion estimation with applications to
large scale visual odometry,
CVPR09(2222-2229).
IEEE DOI
0906
BibRef
Achtelik, M.,
Bachrach, A.,
He, R.,
Prentice, S.,
Roy, N.,
Stereo vision and laser odometry for autonomous helicopters
in GPS-denied indoor environments,
SPIE(7332), pp. 733219, 2009.
DOI Link
BibRef
0000
Hadj-Abdelkader, H.[Hicham],
Malis, E.[Ezio],
Rives, P.[Patrick],
Spherical Image Processing for Accurate Visual Odometry with
Omnidirectional Cameras,
OMNIVIS08(xx-yy).
0810
BibRef
Moreno, F.A.,
Blanco, J.L.,
González, J.,
An Efficient Closed-Form Solution to Probabilistic 6D Visual Odometry
for a Stereo Camera,
ACIVS07(932-942).
Springer DOI
0708
BibRef
Zhu, Z.W.[Zhi-Wei],
Oskiper, T.[Taragay],
Samarasekera, S.[Supun],
Kumar, R.[Rakesh],
Sawhney, H.S.[Harpreet S.],
Ten-fold Improvement in Visual Odometry Using Landmark Matching,
ICCV07(1-8).
IEEE DOI
0710
BibRef
Oskiper, T.[Taragay],
Zhu, Z.W.[Zhi-Wei],
Samarasekera, S.[Supun],
Kumar, R.[Rakesh],
Visual Odometry System Using Multiple Stereo Cameras and Inertial
Measurement Unit,
CVPR07(1-8).
IEEE DOI
0706
BibRef
Kim, J.H.[Jae-Hak],
Hartley, R.I.[Richard I.],
Frahm, J.M.[Jan-Michael],
Pollefeys, M.[Marc],
Visual Odometry for Non-overlapping Views Using Second-Order Cone
Programming,
ACCV07(II: 353-362).
Springer DOI
0711
Motion estimation from mounted cameras that do not overlap.
More (or really less) than stereo.
BibRef
Ni, K.[Kai],
Dellaert, F.[Frank],
Stereo Tracking and Three-Point/One-Point Algorithms:
A Robust Approach in Visual Odometry,
ICIP06(2777-2780).
IEEE DOI
0610
BibRef
Levin, A.,
Szeliski, R.S.,
Visual odometry and map correlation,
CVPR04(I: 611-618).
IEEE DOI
0408
BibRef
Nister, D.,
Naroditsky, O.,
Bergen, J.,
Visual odometry,
CVPR04(I: 652-659).
IEEE DOI
0408
BibRef
Chapter on Optical Flow Field Computations and Use continues in
LiDAR Odometry, Distance Measurments from LiDAR .