Abstract
It is widely accepted that tasks such as quantitative recovery of depth and threedimensional motion require particularly accurate optical velocities computed by robust and reliable algorithms. Future studies should recognize and address this requirement. Although it is acceptable in many cases, the constraint of invariance to motion of the intensity of reflected light does not account for the subtle intensity variations that often must be taken into consideration if optical velocities are to be computed accurately (Verri and Poggio [1]). Therefore, more accurate model of image brightness formation are needed that are computationally feasible.
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References
A. Verri and T. Poggio, Motion Field and Optical Flow: Qualitative Properties, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 11, 1989, pp. 490–498.
A. Tamtaoui and C. Labit, Constrained Disparity and Motion Estimation for 3D TV Image Sequence Coding, Signal Processing: Image Communication, Vol. 4, 1991, pp. 45–54.
A. M. Waxman and J. H. Duncan, Binocular Image Flows, in: Proceedings of the Workshop on Motion: Representation and Analysis, Charleston, SC, pp. 31–38 (1986).
A. Mitiche, A Computational Approach to the Fusion of Stereopsis and Kineopsis, in: Motion Understanding: Robot and Human Vision (W. N. Martin and J. K. Aggarwal, eds.), pp. 8199, Kluwer Academic Publishers (1988).
E. Hildreth, Computations Underlying the Measurement of Visual Motion, Artificial Intelligence, Vol. 23, 1984, pp. 309–354.
A. L. Yuille and N. M. Grzywacz, The Motion Coherence Theory, in: Second International Conference on Computer Vision, Miami, pp. 344–353 (1988).
F. Heitz and P. Bouthemy, Multimodal Estimation of Discontinuous Optical Flow Using Markov Random Fields, INRIA-Rennes Technical Report 561, 1991.
K. Nakayama and S. Shimojo, Intermediate and Higher Order Aspects of Motion Processing: Temporal and Spatial Pooling of Velocity Signals and the Role of Hidden Lines and Surfaces, in: Neural Mechanisms of Visual Perception (D. Lam and C. Gilbert, eds.), pp. 281–296, Portfolio Publishing Company, The Woodlands, TX (1989).
J. Aloimonos, Purposive and Qualitative Active Vision, in: Proceedings of the DARPA Image Understanding Workshop, pp. 816–828 (1990).
J. Aloimonos and Z. Durit, Active Egomotion Estimation: A Qualitative Approach, in: Proceedings of the Second International Conference on Computer Vision, Genoa, pp. 497510 (1992).
J. Aloimonos, I. Weiss, and A. Bandyopadhyay, Active Vision, in: Proceedings of the 1st International Conference on Computer Vision, London, pp. 35–54 (1987).
R. Bajcsy, Active Perception, Proceedings of the IEEE, Vol. 76, No. 8, 1988, pp. 996–1005.
C. M. Brown, Prediction and Cooperation in Gaze Control, Biological Cybernetics, Vol. 63, 1990, pp. 61–70.
G. Sandini and M. Tistarelli, Active Tracking Strategy for Monocular Depth Inference over Multiple Frames, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 12, No. 1, 1990, pp. 13–27.
F. Chaumette and S. Boukir, Structure from Motion Using an Active Vision Paradigm, in: Proceedings of the Eleventh International Conference on Pattern Recognition, The Hague, pp. 41–44 (1992).
A. Bandyopadhyay and D. H. Ballard, Egomotion Perception Using Visual Tracking, Computational Intelligence, Vol. 7, 1991, pp. 39–47.
K. Pahlavan, T. Uhlin, and J. O. Eklundh, Integrating Primary Ocular Processes, in: Proceedings of the Second European Conference on Computer Vision, Genoa, pp. 526–541 (1992).
B. Espiau, F. Chaumette, and P. Rives, A New Approach to Visual Servoing, IEEE Transactions on Robotics and Automation, Vol. 8, No. 3, 1992, pp. 313–326.
J. T. Feddema and O. R. Mitchell, Vision-Guided Servoing with Feature-Based Trajectory Generation, IEEE Transactions on Robotics and Automation,Vol. 5, No. 5, 1989, pp. 691700.
L. E. Weiss and A. C. Sanderson, Dynamic Sensor-Based Control of Robots with Visual Feedback, IEEE Transactions on Robotics and Automation, Vol. 4, 1990, pp. 39–57.
R. D. Rimey and C. M. Brown, Where to Look Next Using a Bayes Net: Incorporating Geometric Constraints, in: Proceedings of the Second European Conference on Computer Vision, Genoa, pp. 542–550 (1992).
J. Pearl, On Evidential Reasoning in a Hierarchy of Hypotheses, Artificial Intelligence, Vol. 28, 1986, pp. 9–15.
B. K. P. Horn and E. J. Weldon, Direct Methods for Recovering Motion, International Journal of Computer Vision, Vol. 2, 1988, pp. 51–76.
C. P. Jerian and R. Jain, Structure and Motion: A Critical Analysis of Methods, IEEE Transactions on Systems, Man, and Cybernetics, Vol. 21, 1991, pp. 572–588.
G. Adiv, Inherent Ambiguities in Recovering 3D Motion and Structure from a Noisy Optical Flow Field, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 11, 1989, pp. 477–489.
G. S. Young and R. Chellappa, Statistical Analysis of Inherent Ambiguities in Recovering 3D Motion from a Noisy Field, in: Proceedings of the 10th International Conference on Pattern Recognition, Atlantic City, pp. 371–377 (1990).
J. L. Barron, A. D. Jepson and J. K. Tsotsos, The Feasibility of Motion and Structure from Noisy Time-Varying Image Velocity Information, International Journal of Computer Vision, Vol. 5, 1990, pp. 239–269.
K. Daniilidis, and H. H. Nagel, Analysis Results on Error Sensitivity of Motion Estimation from Two Views, Image and Vision Computing, Vol. 8, 1990, pp. 297–303.
R. S. Jasinschi, The Properties of Space—Time Sampling and the Extraction of the Optical Flow: the Effects of Motion Uncertainty, Journal of Visual Communications and Image Representation, Vol. 2, 1991, pp. 222–229.
J. Weng, T. S. Huang, and N. Ahuja, 3D Motion Estimation, Understanding, and Prediction from Noisy Images, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 9, No. 3, 1987, pp. 370–389.
Y. Yasumoto and G. Medioni, Robust Estimation of Three-Dimensional Motion Parameters from a Sequence of Image Frames Using Regularization, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 8, No. 4, 1986, pp. 464–471.
T. J. Broida and R. Chellapa, Estimation of Object Motion Parameters from Noisy Images, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 8, No. 1, 1986, pp. 90–99.
H. P. Trivedi, On Computing All the Solutions to the Motion Estimation Problem with Exact and Noisy Data, Image and Vision Computing, Vol. 9, 1991, pp. 229–234.
O. Faugeras, F. Lustman, and G. Toscani, Motion and Structure from Motion from Point and Line Matches, in: Proceedings of the First International Conference on Computer Vision, London, pp. 25–34 (1987).
S. Negandaripour and B. K. P. Horn, Determining 3D Motion of Planar Objects from Image Brightness Measurements, in: Proceedings of the International Joint Conference on Artificial Intelligence, Los Angeles, pp. 898–901 (1985).
S. Negandaripour and S. Lee, Motion Recovery from Image Sequences Using First-order Optical Flow Information, in: Proceedings of the International Conference on Computer Vision, Princeton, NJ, pp. 132–139 (1991).
J. Heel, Direct Estimation of Structure and Motion from Multiple Frames, MIT AI Lab. Memo No. 1190, 1990.
F. Meyer and P. Bouthemy, Estimation of Time-to-Collision Maps from First Order Motion Models and Normal Flows, in: Proceedings of the Eleventh International Conference on Pattern Recognition, The Hague, pp. 78–82 (1992).
J. Aloimonos and C. M. Brown, Direct Processing of Curvilinear Sensor Motion from a Sequence of Perspective Images, in: Proceedings of the IEEE Workshop on Computer Vision: Representation and Analysis, Annapolis, MD, pp. 72–77 (1984).
S. Carlsson, Information in the Geometric Structure of Retinal Flow Field, in: Proceedings of the Second International Conference on Computer Vision, pp. 629–633 (1988).
J. J. Koenderink and A. J. van Doom, Invariant Properties of the Motion Parallax Field due to the Movement of Rigid Bodies Relative to an Observer, Optica Acta, Vol. 22, 1975, pp. 773–791.
J. J. Koenderink, Optical Flow, Vision Research, Vol. 26, No. 1, 1986, pp. 161–180.
A. Verri, F. Girosi, and V. Torre, Mathematical Properties of the Two-Dimensional Motion Field–from Singular Points to Motion Parameters, Journal of the Optical Society of America A, Vol. 6, No. 5, 1989, pp. 698–712.
W. B. Thompson and J. K. Kearney, Inexact vision, in: Proceedings of the IEEE Workshop on Motion: Representation and Analysis, Charleston, SC, pp. 15–21 (1986).
R. C. Nelson and J. Aloimonos, Obstacle Avoidance Using Flow Field Divergence, IEEE Transactions on Pattern Analysis and Machine Intelligence,Vol. 11, No. 10, 1989, pp. 11021106.
H. H. Nagel, From Image Sequences towards Conceptual Descriptions, Image and Vision Computing, Vol. 6, No. 2, 1988, pp. 59–74.
W. Burger and B. Bhanu, Qualitative Motion Understanding, in: Proceedings of the International Joint Conference on Artificial Intelligence, pp. 819–821 (1987).
E. François and R. Bouthemy, Derivation of Qualitative Information in Motion Analysis, Image and Vision Computing, Vol. 8, No. 4, 1990, pp. 279–287.
W. B. Thompson and T. G. Pong, Detecting Moving Objects, International Journal of Computer Vision, Vol. 4, 1990, pp. 39–57.
R. C. Nelson, Qualitative Detection of Motion by a Moving Observer, International Journal of Computer Vision, Vol. 7, No. I, 1991, pp. 33–46.
M. E. Spetsakis and J. Aloimonos, Optimal Motion Estimation, in: IEEE Workshop on Visual Motion, Irvine, CA, pp. 229–237 (1989).
M. Subbarao, Interpretation of Image Flow: A Spatio-Temporal Approach, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 11, No. 3, 1989, pp. 266–278.
H. Shariat and K. Price, Motion Estimation with More than Two Frames, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 12, No. 5, 1990, pp. 417–434.
T. J. Broida and R. Chellappa, Estimating the Kinematics and Structure of a Rigid Object from a Sequence of Monocular Images, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 13, No. 6, 1991, pp. 497–513.
L. Matthies, T. Kanade, and R. Szeleski, Kalman Filter Based Algorithms for Estimating Depth from Image Sequences, International Journal of Computer Vision, Vol. 3, 1989, pp. 209–236.
J. J. Wu, R. E. Rink, T. M. Caelli, and V. G. Gourishankar, Recovery of the 3D Location and Motion of a Rigid Object through Camera Image: An Extended Kalman Filter Approach, International Journal of Computer Vision, Vol. 3, 1991, pp. 373–394.
R. Hummel and V. Sundareswaran, Motion Parameter Estimation from Global Flow Field Data, New York University, Courant Institute Technical Report, 1991.
B. Espiau and P. Rives, Closed-Loop Recursive Estimation of 3D Features for a Mobile Vision System, in: Proceedings of the IEEE Conference on Robotics and Automation, Raleigh, NC, pp. 1436–1443 (1987).
J. L. Crowley, P. Stelmaszyk, T. Skordas, and P. Puget, Measurement and Integration of 3D Structures by Tracking Edge Lines, International Journal of Computer Vision, Vol. 8, No. 1, 1992, pp. 29–52.
J. A. Webb and J. K. Aggarwal, Structure from Motion of Rigid and Jointed Objects, Artificial Intelligence, Vol. 19, 1982, pp. 107–130.
B. Horowitz and A. Pentland, Recovery of Non-Rigid Motion and Structure, in: Proceedings of the Computer Vision and Pattern Recognition Conference, Hawaii, pp. 325–330 (1991).
J. Leese, C. Novak, and B. Clark, An Automated Technique for Obtaining Cloud Motion from Geosynchronous Satellite Data using Cross-Correlation, Journal of Applied Meteorology, Vol. 10, 1971, pp. 118–132.
G. E. Mailloux, F. Langlois, P. L. Simard, and M. Bertrand, Restoration of the Velocity Field of the Heart from Two-Dimensional Echocardiograms, IEEE Transactions on Medical Imaging, Vol. 8, No. 2, 1989, pp. 143–153.
S. K. Mishra, D. B. Goldgof, and T. S. Huang, Motion Analysis and Epicardial Deformation Estimation from Angiography Data, in: Proceedings of the Computer Vision and Pattern Recognition Conference, Hawaii, pp. 331–336 (1991).
D. Terzopoulos, Dynamic 3D Models with Local and Global Deformations: Deformable Superquadrics, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 13, No. 7, 1991, pp. 703–714.
A. P. Pentland, Automatic Extraction of Deformable Part Models, International Journal of Computer Vision, Vol. 4, 1990, pp. 107–126.
A. P. Pentland and B. Horowitz, Recovery of Non Rigid Motion and Structure, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 13, No. 7, 1991, pp. 730–742.
I. Herlin and N. Ayache, Feature Extraction and Analysis Methods for Sequences of Ultrasound Images, in: Proceedings of the Second European Conference on Computer Vision, Genoa, pp. 43–57 (1992).
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Mitiche, A. (1994). Conclusion: Current Issues in Analysis of Visual Motion. In: Computational Analysis of Visual Motion. Advances in Computer Vision and Machine Intelligence. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-9785-5_9
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