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A New Approach to Tracking 3D Objects in 2D Image Sequences (1994)  (Make Corrections)  (3 citations)
Michael Chan, Dimitri Metaxas, Sven Dickinson
National Conference on Artificial Intelligence



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Abstract: We present a new technique for tracking 3D objects from 2D image sequences through the integration of qualitative and quantitative techniques. The deformable models are initialized based on a previously developed part-based qualitative shape segmentation system. Using a physics-based quantitative approach, objects are subsequently tracked without feature correspondence based on generalized forces computed from the stereo images. The automatic prediction of possible edge occlusion and... (Update)

Context of citations to this paper:   More

...would more effectively prevent network contours from converging. 4. 2 Quantitative Object Tracking Our approach to quantitative tracking [4, 5] makes use of our frameworks for qualitative and quantitative shape recovery described in previous sections, as well as a physics based...

.... ambiguous or are heavily occluded, the system must move to a better viewpoint ( 20] and, while moving, the system must track the objects [22, 16]. We have successfully addressed each of these problems within the framework of our hybrid object centered viewer centered...

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Integrating Qualitative and Quantitative Object.. - Dickinson, Metaxas   (Correct)

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BibTeX entry:   (Update)

M. Chan, D. Metaxas, and S. Dickinson. A new approach to tracking 3-D objects in 2-D image sequences. In Proceedings, AAAI '94, Seattle, WA, August 1994. http://citeseer.ist.psu.edu/chan94new.html   More

@inproceedings{ chan94new,
    author = "Michael Chan and Dimitris N. Metaxas and Sven J. Dickinson",
    title = "A New Approach to Tracking 3D Objects in 2D Image Sequences",
    booktitle = "National Conference on Artificial Intelligence",
    pages = "960-965",
    year = "1994",
    url = "citeseer.ist.psu.edu/chan94new.html" }
Citations (may not include all citations):
1386   Snakes: Active Contour Models (context) - Kass, Witkin et al. - 1988
130   Fitting Parameterized Three-Dimensional Models to Images - Lowe - 1991
113   Shape and Nonrigid Motion Estimation Through Physics-Based S.. (context) - Metaxas, Terzopoulos - 1993
99   Recovery of Nonrigid Motion and Structure (context) - Pentland, Horowitz - 1991
80   Visual Tracking of Known ThreeDimensional Objects (context) - Gennery - 1992
78   Shape Recovery Using Distributed Aspect Matching (context) - Dickinson, Pentland et al.
77   Dynamic 3D Models with Local and Global Deformations: Deform.. (context) - Terzopoulos, Metaxas - 1991
51   Motion Estimation from a Monocular Image Sequence (context) - Broida, Chandrashekhar et al. - 1990
49   Constraints on Deformable Models: Recovering 3D Shape and No.. (context) - Terzopoulos, Witkin et al. - 1988
47   Tracking Line Segments (context) - Deriche, Faugeras - 1990
45   Applications of Dynamic Monocular Machine Vision (context) - Dickmanns, Graefe - 1988
34   From Volumes to Views: An Approach to 3D Object Recognition (context) - Dickinson, Pentland et al.
34   AffineInvariant Contour Tracking with Automatic Control of S.. (context) - Blake, Curwen et al. - 1993
32   Measurement of Nonrigid Motion Using Contour Shape Descripto.. (context) - Duncan, Owen et al. - 1991
17   Integration of Quantitative and Qualitative Techniques for D.. (context) - Metaxas, Dickinson - 1993
5   Physically-Based and Probabilistic Modeling for Computer Vis.. (context) - Szeliski, Terzopoulos - 1991
4   Analysis and Visualization of Nonrigid Object Motion (context) - Huang - 1990
2   Real-time (context) - Verghese, Gale et al. - 1990
1   Motion-Based Motion Analysis: Motion from Motion (context) - Thompson, Mundy - 1988

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