18.3.4.7 Moving Object Extraction with Moving Cameras

Chapter Contents (Back)
Object Segmentation. Sequence Analysis. Motion Segmentation.

François, E.[Edouard], Bouthemy, P.[Patrick],
Motion Segmentation and Qualitative Dynamic Scene Analysis from an Image Sequence,
IJCV(10), No. 2, May 1993, pp. XX.
Springer DOI BibRef 9305
Earlier:
Multiframe-Based Identification of Mobile Components of a Scene with a Moving Camera,
CVPR91(166-172).
IEEE DOI Segment based on differences then analyze the regions. BibRef

François, E.[Edouard], Bouthemy, P.[Patrick],
The Derivation of Qualitative Information in Motion Analysis,
IVC(8), No. 4, November 1990, pp. 279-288. BibRef 9011
And: ECCV90(226-230).
Springer DOI 9004
BibRef

Francois, E.,
Interpretation Qualitative Du Mouvement a Partir d'une Sequence d'Images,
Ph.D.Universite de Rennes I, 1991. BibRef 9100

Meyer, F.G., and Bouthemy, P.,
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IEEE DOI BibRef 9300

Letang, J.M., Rebuffel, V., and Bouthemy, P.,
Motion Detection Robust to Perturbations: A Statistical Regularization and Temporal Integration Framework,
ICCV93(21-30).
IEEE DOI BibRef 9300
Earlier:
Motion Detection Based on a Temporal Multiscale Approach,
ICPR92(I:65-68).
IEEE DOI Multi-scale (temporal) decomposition followed by change detection to track moving objects. BibRef

Hennebert, C., Rebuffel, V., Bouthemy, P.,
A Hierarchical Approach for Scene Segmentation Based on 2D Motion,
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IEEE DOI 9608
(LETI, DSYS) BibRef

Bouthemy, P., and Lalande, P.,
Detection and Tracking of Moving Objects Based on a Statistical Regularization Method in Space and Time,
ECCV90(307-311).
Springer DOI Find the moving objects (cars) with a stationary camera. See also Region-Level Motion-Based Graph Representation and Labeling for Tracking a Spatial Image Partition, A. BibRef 9000

Bouthemy, P., Santillana Rivero, J.,
A Hierarchical Likelihood Approach for Region Segmentation According to Motion-Based Criteria,
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Thakoor, N.S.[Ninad S.], Gao, J.X.[Jean X.],
Automatic Video Object Extraction With Camera In Motion,
IJIG(8), No. 4, October 2008, pp. 573-600. 0804
BibRef
Earlier:
Branch-and-bound hypothesis selection for two-view multiple structure and motion segmentation,
CVPR08(1-6).
IEEE DOI 0806
BibRef
Earlier:
Automatic Video Object Shape Extraction and its Classification with Camera in Motion,
ICIP05(III: 437-440).
IEEE DOI 0512
See also Multistage Branch-and-Bound Merging for Planar Surface Segmentation in Disparity Space. BibRef

Thakoor, N.S.[Ninad S.], Gao, J.X.[Jean X.], Devarajan, V.,
Multibody Structure-and-Motion Segmentation by Branch-and-Bound Model Selection,
IP(19), No. 6, June 2010, pp. 1393-1402.
IEEE DOI 1006
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Gao, J.X.[Jean X.], Thakoor, N.S.[Ninad S.], Jung, S.Y.[Sung-Yong],
A motion field reconstruction scheme for smooth boundary video object segmentation,
ICIP04(I: 381-384).
IEEE DOI 0505
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Cho, J.S.[Jae-Soo],
Apparatus and method for controlling a camera using a video compression algorithm,
US_Patent7,248,286, Jul 24, 2007
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Wang, J., Patel, N.V., Grosky, W.I., Fotouhi, F.,
Moving Camera Moving Object Segmentation in Compressed Video Sequences,
IJIG(9), No. 4, October 2009, pp. 609-627.
DOI Link 0911
BibRef

Zhang, G.F.[Guo-Feng], Jia, J.Y.[Jia-Ya], Hua, W.[Wei], Bao, H.J.[Hu-Jun],
Robust Bilayer Segmentation and Motion/Depth Estimation with a Handheld Camera,
PAMI(33), No. 3, March 2011, pp. 603-617.
IEEE DOI 1102
High quality moving foreground. Non-planar background. BibRef

Zhang, G.F.[Guo-Feng], Jia, J.Y.[Jia-Ya], Xiong, W.[Wei], Wong, T.T.[Tien-Tsin], Heng, P.A.[Pheng-Ann], Bao, H.J.[Hu-Jun],
Moving Object Extraction with a Hand-held Camera,
ICCV07(1-8).
IEEE DOI 0710
BibRef

Kim, S.W.[Soo Wan], Yun, K.[Kimin], Yi, K.M.[Kwang Moo], Kim, S.J.[Sun Jung], Choi, J.Y.[Jin Young],
Detection of moving objects with a moving camera using non-panoramic background model,
MVA(24), No. 5, July 2013, pp. 1015-1028.
Springer DOI 1306
BibRef

Paul, J.[Johny], Laika, A.[Andreas], Claus, C.[Christopher], Stechele, W.[Walter], Auf, A.E.[Adam El_Sayed], Maehle, E.[Erik],
Real-time motion detection based on SW/HW-codesign for walking rescue robots,
RealTimeIP(8), No. 4, December 2013, pp. 353-368.
Springer DOI 1312
BibRef

Zhang, Y.H.[Yin-Hui], He, Z.F.[Zi-Fen], Liu, C.Y.[Chang-Yu],
Robust Segmentation of Highly Dynamic Scene with Missing Data,
IEICE(E98-D), No. 1, January 2015, pp. 201-205.
WWW Link. 1503
BibRef

Zhang, Y.H.[Yin-Hui], He, Z.F.[Zi-Fen],
Large Displacement Dynamic Scene Segmentation through Multiscale Saliency Flow,
IEICE(E99-D), No. 7, July 2016, pp. 1871-1876.
WWW Link. 1608
See also Global optimization of wavelet-domain hidden Markov tree for image segmentation. BibRef

Zhang, Y.H.[Yin-Hui], He, Z.F.[Zi-Fen],
Video Object Segmentation of Dynamic Scenes with Large Displacements,
IEICE(E98-D), No. 9, September 2015, pp. 1719-1723.
WWW Link. 1509
BibRef

Zhang, Y.H.[Yin-Hui], He, Z.F.[Zi-Fen],
Semantic Motion Signature for Segmentation of High Speed Large Displacement Objects,
IEICE(E100-D), No. 1, January 2017, pp. 220-224.
WWW Link. 1701
BibRef

Zhang, Y.H.[Yin-Hui], Abdel-Mottaleb, M.[Mohamed], He, Z.F.[Zi-Fen],
Nonlinear Regression of Saliency Guided Proposals for Unsupervised Segmentation of Dynamic Scenes,
IEICE(E99-D), No. 2, February 2016, pp. 467-474.
WWW Link. 1604
BibRef

Zhang, Y.H.[Yin-Hui], Abdel-Mottaleb, M.[Mohamed], He, Z.F.[Zi-Fen],
Unsupervised segmentation of highly dynamic scenes through global optimization of multiscale cues,
PR(48), No. 11, 2015, pp. 3477-3487.
Elsevier DOI 1506
Image sequence segmentation BibRef

Chattopadhyay, C.[Chiranjoy], Das, S.[Sukhendu],
Prominent moving object segmentation from moving camera video shots using iterative energy minimization,
SIViP(9), No. 8, November 2015, pp. 1927-1934.
WWW Link. 1511
BibRef
Earlier:
STAR: A Content Based Video Retrieval system for moving camera video shots,
NCVPRIPG13(1-4)
IEEE DOI 1408
content-based retrieval BibRef

Chattopadhyay, C.[Chiranjoy], Das, S.[Sukhendu],
Use of trajectory and spatiotemporal features for retrieval of videos with a prominent moving foreground object,
SIViP(10), No. 1, February 2016, pp. 319-326.
WWW Link. 1601
BibRef

Chattopadhyay, C.[Chiranjoy], Das, S.[Sukhendu],
Supervised framework for automatic recognition and retrieval of interaction: a framework for classification and retrieving videos with similar human interactions,
IET-CV(10), No. 3, 2016, pp. 220-227.
DOI Link 1604
learning (artificial intelligence) BibRef

Okade, M.[Manish], Biswas, P.K.[Prabir Kumar],
A novel moving object segmentation framework utilizing camera motion recognition for H.264 compressed videos,
JVCIR(36), No. 1, 2016, pp. 199-212.
Elsevier DOI 1603
Block motion vectors BibRef

Hu, W., Yang, Y., Zhang, W., Xie, Y.,
Moving Object Detection Using Tensor-Based Low-Rank and Saliently Fused-Sparse Decomposition,
IP(26), No. 2, February 2017, pp. 724-737.
IEEE DOI 1702
decomposition BibRef

Rozantsev, A.[Artem], Lepetit, V.[Vincent], Fua, P.[Pascal],
Detecting Flying Objects Using a Single Moving Camera,
PAMI(39), No. 5, May 2017, pp. 879-892.
IEEE DOI 1704
BibRef
Earlier:
Flying objects detection from a single moving camera,
CVPR15(4128-4136)
IEEE DOI 1510
Aircraft BibRef

Chen, T., Lu, S.,
Object-Level Motion Detection From Moving Cameras,
CirSysVideo(27), No. 11, November 2017, pp. 2333-2343.
IEEE DOI 1712
Adaptive optics, Cameras, Histograms, Motion detection, Motion segmentation, Optical imaging, Semantics, moving camera BibRef

El Tantawy, A.[Agwad], Shehata, M.S.[Mohamed S.],
MARO: matrix rank optimization for the detection of small-size moving objects from aerial camera platforms,
SIViP(12), No. 4, May 2018, pp. 641-649.
WWW Link. 1805
BibRef
Earlier:
A novel method for segmenting moving objects in aerial imagery using matrix recovery and physical spring model,
ICPR16(3898-3903)
IEEE DOI 1705
BibRef
Earlier:
UT-MARO: Unscented Transformation and Matrix Rank Optimization for Moving Objects Detection in Aerial Imagery,
ISVC15(I: 275-284).
Springer DOI 1601
BibRef
And:
Moving object detection from moving platforms using Lagrange multiplier,
ICIP15(2586-2590)
IEEE DOI 1512
PCA. Cameras, Image segmentation, Matrix decomposition, Object segmentation, Optimization, Robustness, Springs BibRef


Heo, B., Yun, K., Choi, J.Y.,
Appearance and motion based deep learning architecture object detection in moving camera,
ICIP17(1827-1831)
IEEE DOI 1803
Cameras, Contamination, Dynamics, Machine learning, Object detection, Robustness, Training, Moving object detection, deep learning, moving camera BibRef

Bideau, P.[Pia], Learned-Miller, E.[Erik],
It's Moving! A Probabilistic Model for Causal Motion Segmentation in Moving Camera Videos,
ECCV16(VIII: 433-449).
Springer DOI 1611
BibRef

Chung, W.[Won_Taek], Kim, Y.[Yong_Hyun], Kim, Y.J.[Yong-Joong], Kim, D.[Dai_Jin],
A two-stage foreground propagation for moving object detection in a non-stationary,
AVSS16(187-193)
IEEE DOI 1611
Adaptation models BibRef

Lopez-Perez, J.J.[Jose J.], Ayala-Ramirez, V.[Victor], Hernandez-Belmonte, U.H.[Uriel H.],
Dynamic Object Detection and Representation for Mobile Robot Application,
MCPR16(84-93).
Springer DOI 1608
BibRef

Yun, K.[Kimin], Choi, J.Y.[Jin Young],
Robust and Fast Moving Object Detection in a Non-Stationary Camera Via Foreground Probability Based Sampling,
ICIP15(4897-4901)
IEEE DOI 1512
Foreground probability based sampling See also Robust Moving Object Detection Against Fast Illumination Change. BibRef

Yi, K.M.[Kwang Moo], Yun, K.[Kimin], Kim, S.W.[Soo Wan], Chang, H.J.[Hyung Jin], Choi, J.Y.[Jin Young],
Detection of Moving Objects with Non-stationary Cameras in 5.8ms: Bringing Motion Detection to Your Mobile Device,
IWMV13(27-34)
IEEE DOI 1309
gaussian model; mobile phone; motion detection BibRef

Battistone, F.[Francesco], Petrosino, A.[Alfredo], Sanniti di Baja, G.[Gabriella],
GRUNTS: Graph Representation for UNsupervised Temporal Segmentation,
CIAP15(I:225-235).
Springer DOI 1511
BibRef

Liang, X.F.[Xue-Feng], Zhang, C.[Cuicui], Matsuyama, T.[Takashi],
Inlier Estimation for Moving Camera Motion Segmentation,
ACCV14(IV: 352-367).
Springer DOI 1504
BibRef

Koutlemanis, P., Zabulis, X., Ntelidakis, A., Argyros, A.A.,
Foreground Detection with a Moving RGBD Camera,
ISVC13(I:216-227).
Springer DOI 1310
BibRef

Xiang, X.[Xiang],
An Attempt to Segment Foreground in Dynamic Scenes,
ISVC11(I: 124-134).
Springer DOI 1109
BibRef

Chen, Y.[Yang], Khosla, D.[Deepak], Huber, D.[David], Kim, K.[Kyungnam], Cheng, S.Y.[Shinko Y.],
A Neuromorphic Approach to Object Detection and Recognition in Airborne Videos with Stabilization,
ISVC11(II: 126-135).
Springer DOI 1109
BibRef

Cheng, S.Y.[Shinko Y.], Chen, Y.[Yang], Khosla, D.[Deepak], Kim, K.[Kyungnam],
Optimal Multiclass Classifier Threshold Estimation with Particle Swarm Optimization for Visual Object Recognition,
ISVC11(II: 536-544).
Springer DOI 1109
BibRef

Hori, M.[Maiya], Takahashi, H.[Hideyuki], Kanbara, M.[Masayuki], Yokoya, N.[Naokazu],
Removal of Moving Objects and Inconsistencies in Color Tone for an Omnidirectional Image Database,
CVMAR10(62-71).
Springer DOI 1109
BibRef

Kim, J.[Jiman], Ye, G.[Guensu], Kim, D.J.[Dai-Jin],
Moving object detection under free-moving camera,
ICIP10(4669-4672).
IEEE DOI 1009
BibRef

Uchiyama, H.[Hiroyuki], Deguchi, D.[Daisuke], Takahashi, T.[Tomokazu], Ide, I.[Ichiro], Murase, H.[Hiroshi],
Removal of Moving Objects from a Street-View Image by Fusing Multiple Image Sequences,
ICPR10(3456-3459).
IEEE DOI 1008
BibRef

Lin, C.C.[Chung-Ching], Wolf, M.[Marilyn],
Dynamic Multi-vehicle Detection and Tracking from a Moving Platform,
SISM13(781-787)
IEEE DOI 1309
BibRef
Earlier:
Monocular Online Learning for Road Region Labeling and Object Detection from a Moving Platform,
ISVC11(II: 456-465).
Springer DOI 1109
BibRef
Earlier:
Detecting Moving Objects Using a Camera on a Moving Platform,
ICPR10(460-463).
IEEE DOI 1008
MCMC; detection; moving camera; particle filtering; superpixel; tracking BibRef

Sun, S.W.[Shih-Wei], Huang, F.[Fay], Liao, H.Y.M.[Hong-Yuan Mark],
Data-Driven Foreground Object Detection from a Non-stationary Camera,
ICPR10(3053-3056).
IEEE DOI 1008
BibRef

Escudero-Vinolo, M.[Marcos], Bescos, J.[Jesus],
A robust framework for region based video object segmentation,
ICIP10(3461-3464).
IEEE DOI 1009
BibRef

Tiburzi, F.[Fabrizio], Escudero-Vinolo, M.[Marcos], Bescos, J.[Jesus], Martinez, J.M.[Jose M.],
A ground truth for motion-based video-object segmentation,
ICIP08(17-20).
IEEE DOI 0810
BibRef

Escudero, M.[Marcos], Tiburzi, F.[Fabrizio], Bescos, J.[Jesus],
MPEG video object segmentation under camera motion and multimodal backgrounds,
ICIP08(2668-2671).
IEEE DOI 0810
BibRef

Micheloni, C.[Christian], Foresti, G.L.[Gian Luca], Alberti, E.,
A new feature clustering method for object detection with an active camera,
ICIP04(IV: 2587-2590).
IEEE DOI 0505
BibRef

Woelk, F.[Felix], Koch, R.[Reinhard],
Fast Monocular Bayesian Detection of Independently Moving Objects by a Moving Observer,
DAGM04(27-35).
Springer DOI 0505
BibRef

Dahyot, R., Charbonnier, P., Heitz, F.,
Unsupervised Statistical Detection of Changing Objects in Camera-in-motion Video,
ICIP01(I: 638-641).
IEEE DOI 0108
BibRef

Frazier, J., and Nevatia, R.,
Detecting Moving Objects from a Moving Platform,
DARPA90(348-355). BibRef 9000 USC Computer VisionUsed the CLM (of Jain) and an estimate of the FOE to find moving regions in the image. BibRef

Chapter on Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion continues in
Background Detection, Background Model .


Last update:Jun 23, 2018 at 14:58:54