18.6.1.4 More Direct Ego Motion Computation

Chapter Contents (Back)
Motion, Parameters. Motion, Observer. Ego Motion.

Fermüller, C., Aloimonos, Y.,
Qualitative Egomotion,
IJCV(15), No. 1-2, June 1995, pp. 7-29.
Springer DOI
See also Vision and Action. BibRef 9506

Aloimonos, Y., Duric, Z.,
Active Egomotion Estimation: A Qualitative Approach,
ECCV92(497-510).
Springer DOI BibRef 9200

Vieville, T., Clergue, E., Facao, P.E.D.,
Computation of Ego Motion Using the Vertical Cue,
MVA(8), No. 1, 1995, pp. 41-52.
Springer DOI BibRef 9500
Earlier:
Computation of Ego-Motion and Structure from Visual an Inertial Sensor Using the Vertical Cue,
ICCV93(591-598).
IEEE DOI BibRef

Sakai, Y., Uno, T., Takagi, J., Yamashita, T.,
Optical Spatial Filter Sensor for Ground Speed,
OptRev(2), No. 1, January-February 1995, pp. 65-67. BibRef 9501

da Vitoria Lobo, N., and Tsotsos, J.K.,
Computing Egomotion and Detecting Independent Motion from Image Motion Using Collinear Points,
CVIU(64), No. 1, July 1996, pp. 21-52. 9608

DOI Link BibRef
Earlier:
Computing Egomotion and Shape from Image Motion Using Colinear Points,
VF91(175-185). BibRef
And:
Using Collinear Points to Compute Egomotion and Detect Nonrigidity,
CVPR91(344-350).
IEEE DOI Remove the effect of rotation, the the translation effects are straight lines. BibRef

Srinivasan, M.V., Venkatesh, S., Hosie, R.,
Qualitative Estimation of Camera Motion Parameters from Video Sequences,
PR(30), No. 4, April 1997, pp. 593-606.
Elsevier DOI 9705
BibRef

Royden, C.S.,
Mathematical-Analysis of Motion-Opponent Mechanisms Used in the Determination of Heading and Depth,
JOSA-A(14), No. 9, September 1997, pp. 2128-2143. 9709
BibRef

Wang, R.X.F.[Ran-Xiao Frances], Cutting, J.E.[James E.],
A Probabilistic Model for Recovering Camera Translation,
CVIU(76), No. 3, December 1999, pp. 205-212. 0001

DOI Link BibRef

Wei, J.[Jie], Li, Z.N.[Ze-Nian],
On Active Camera Control and Camera Motion Recovery with Foveate Wavelet Transform,
PAMI(23), No. 8, August 2001, pp. 896-903.
IEEE DOI 0109
BibRef
Earlier: A2, A1:
Foveate Wavelet Transform for Camera Motion Recovery From Videos,
ICPR98(Vol II: 1445-1448).
IEEE DOI 9808
Variable resolution (scale-space) representation technique. Preserves linearity, orientation selective. BibRef

Zhai, G.Y.[Guang-Yao], Liu, L.[Liang], Zhang, L.[Linjian], Liu, Y.[Yong], Jiang, Y.[Yunliang],
PoseConvGRU: A Monocular Approach for Visual Ego-motion Estimation by Learning,
PR(102), 2020, pp. 107187.
Elsevier DOI 2003
Ego-motion, Pose estimation, Deep learning, Recurrent Convolutional Neural Networks, Data augmentation BibRef


Jiang, S., Campbell, D., Liu, M., Gould, S., Hartley, R.I.,
Joint Unsupervised Learning of Optical Flow and Egomotion with Bi-Level optimization,
3DV20(682-691)
IEEE DOI 2102
Optical imaging, Optimization, Cameras, Geometrical optics, Estimation, Optical losses, Geometry, optical flow, ego motion BibRef

Teller, S.J.[Seth J.],
Pervasive Multi-Sensor Egomotion Estimation for Direct Interaction and Unstructured Robotics,
VMV04(279). 0411
BibRef

Sánchez, P.[Pedro], Yáńez-Márquez, C.[Cornelio], Pecero, J.[Jonathan], Ramírez, A.[Apolinar],
Egomotion Estimation as an Appearance-Based Classification Problem,
CIARP06(743-752).
Springer DOI 0611
BibRef

Svoboda, T.[Tomáš], Sturm, P.F.[Peter F.],
A badly calibrated camera in ego-motion estimation: Propagation of uncertainty,
CAIP97(183-190).
Springer DOI 9709
BibRef
Earlier:
What Can Be Done with a Badly Calibrated Camera in Ego-Motion Estimation?,
TRCTU-CMP-1996-01, Czech Technical University, Center for Machine Perception, December 1996.
HTML Version. visual motion, error propagation, essential matrix, stereo vision, ego-motion estimation, statistical analysis BibRef

Lawn, J.M., Cipolla, R.,
Reliable Extraction of the Camera Motion Using Constraints on the Epipole,
ECCV96(II:161-173).
Springer DOI Epipole is direction of camera motion.
PS File. BibRef 9600

Coombs, D., and Roberts, K.J.[Karen],
Centering Behavior Using Peripheral Vision,
CVPR93(440-445).
IEEE DOI BibRef 9300
Earlier:
'Bee-bot': Using Peripheral Optical Flow to Avoid Obstacles,
SPIE(1825), Intelligent Robots and Computer Vision XI: Algorithms, Techniques, and Active Vision, Boston, MA, November 1992. The low-resolution vision is used to center between walls.
PS File. BibRef

Arbogast, E., Mohr, R.,
An Egomotion Algorithm Based on the Tracking of Arbitrary Curves,
ECCV92(467-475).
Springer DOI BibRef 9200

Sundareswaran, V.,
A Fast Method to Estimate Sensor Translation,
ECCV92(253-257).
Springer DOI BibRef 9200

Mendelsohn, J., Simoncelli, E.P.,
Acceleration-Limited Egomotion Estimation,
UPennAugust 1996. GRASP Laboratory Technical Report BibRef 9608

Bandopadhy, A.[Amit], Chandra, B.[Barun], and Ballard, D.H.,
Egomotion Using Active Vision,
CVPR86(498-503). BibRef 8600
And:
Active Navigation: Tracking an Environmental Point Considered Beneficial,
Motion86(23-29). Nothing exciting, mix binocular vision and monocular. BibRef

Chapter on Optical Flow Field Computations and Use continues in
Focus of Expansion and Other Features .


Last update:Mar 16, 2024 at 20:36:19