Abstract
We present a method for figure-ground segregation of moving objects from monocular video sequences. The approach is based on tracking extracted contour fragments, in contrast to traditional approaches which rely on feature points, regions, and unorganized edge elements. Specifically, a notion of similarity between pairs of curve fragments appearing in two adjacent frames is developed and used to find the curve correspondence. This similarity metric is elastic in nature and in addition takes into account both a novel notion of transitions in curve fragments across video frames and an epipolar constraint. This yields a performance rate of 85% correct correspondence on a manually labeled set of frame pairs. The retrieved curve correspondence is then used to group curves in each frame into clusters based on the pairwise similarity of how they transform from one frame to the next. Results on video sequences of moving vehicles show that using curve fragments for tracking produces a richer segregation of figure from ground than current region or feature-based methods.
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References
Adams, R., Bischof, L.: Seeded region growing. PAMI 16(6), 641–647 (1994)
Canny, J.: A computational approach to edge detection. PAMI 8, 679–698 (1986)
Comaniciu, D., Ramesh, V., Meer, P.: Real-time tracking of nonrigid objects using mean shift. In: CVPR, Hilton Head Island, South Carolina, pp. 2:142–149 (2000)
Deriche, R., Giraudon, G.: A computational approach for corner and vertex detection. In: IJCV, pp. 167–187 (1993)
Erdem, C.E., Tekalp, A., Sankur, B.: Video object tracking with feedback of performance measures. In: Proc. IEEE Conf. on CVPR, December 2001, pp. 593–600 (2001)
Ferrari, V., Tuytelaars, T., van Gool, L.: Real-time affine region tracking and coplanar grouping. In: Proc. IEEE Conf. on CVPR, Kauai, Hawaii, pp. 226–233 (2001)
Folta, F., Eycken, L.V., van Gool, L.: Shape extraction using temporal continuity. In: Proc. European Workshop on Image Analysis for Multimedia Interactive Services of the IEEE conference on CVPR, pp. 69–74 (1997)
Freedman, D.: Effective tracking through tree search. IEEE Trans. on Pattern Analysis and Machine Intelligence 25, 604–615 (2003)
Gold, S., Rangarajan, A., Mjolsness, E.: Learning with preknowledge:clustering with point and graph matching distance measures. Neural Computation 8(4), 787–804 (1996)
Hager, G., Belhumeur, P.: Efficient region tracking with parametric models of geometry and illumination. PAMI 20(10), 1025–1039 (1998)
Harris, C.: Determination of ego-motion from matched points. In: IJCV, pp. 189–192 (1993)
Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision. Cambridge University Press, Cambridge (2000)
Huttenlocher, D.P., Klanderman, G.A., Rucklidge, W.J.: Comparing images using the Hausdorff distance. PAMI 15, 850–863 (1993)
Isard, M., Blake, A.: Condensation - conditional density propagation for visual tracking. In: IJCV, vol. 29, pp. 2–28 (1998)
Kass, M., Witkin, A., Terzopoulos, D.: Snakes: Active contour models. International Journal of Computer Vision 1(4), 321–331 (1987)
Koller, D., Weber, J., Malik, J.: Robust multiple car tracking with occlusion reasoning. In: Proceedings of the Third European Conference on Computer Vision, vol. I, Springer, Heidelberg (1994)
Lindenberg, T.: Feature detection with automatic scale detection. IJCV 30(2), 77–116 (1998)
McBride, J.: Archaeological fragment reassembly using curve matching. Master’s disseration,Brown University,Providence,USA (2003)
Moravec, H.P.: Visual mapping by a robot rover. In: Proc. of the 6th International Joint Conference on Artificial Intelligence, pp. 598–600 (1979)
Paragios, N., Deriche, R.: A pde-based level set approach for detection and tracking of moving objects. In: Proc. IJCV, Bombay, India, Janurary (1998)
Rothwell, C., Mundy, J., Hoffman, W., Nguyen, V.-D.: Driving vision by topology. In: IEEE Intl. Symosium on Computer Vision, pp. 395–400 (1995)
Sebastian, T., Klein, P., Kimia, B.: On aligning curves. IEEE Trans. PAMI 25(1), 116–125 (2003)
Sharvit, D., Chan, J., Tek, H., Kimia, B.B.: Symmetry-based indexing of image databases. JVCIR 9(4), 366–380 (1998)
Shi, J., Tomasi, C.: Good features to track. In: Proc. of the IEEE conference on CVPR, pp. 593–600 (1994)
Younes, L.: Computable elastic distance between shapes. SIAM Journal of Applied Mathematics 58, 565–586 (1998)
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Jain, V., Kimia, B.B., Mundy, J.L. (2006). Segregation of Moving Objects Using Elastic Matching. In: MacLean, W.J. (eds) Spatial Coherence for Visual Motion Analysis. SCVMA 2004. Lecture Notes in Computer Science, vol 3667. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11676959_7
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DOI: https://doi.org/10.1007/11676959_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-32533-8
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