Local detection of occlusion boundaries in video

Author:

Stein Andrew N.,Hebert Martial

Publisher

Elsevier BV

Subject

Computer Vision and Pattern Recognition,Signal Processing

Reference37 articles.

1. A. Stein, M. Hebert, Incorporating background invariance into feature-based object recognition, in: IEEE Workshop on Applications of Computer Vision (WACV), 2005, pp. 37–44.

2. Learning to detect natural image boundaries using local brightness, color, and texture cues;Martin;IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI),2004

3. B.A. Maxwell, S.J. Brubaker, Texture edge detection using the compass operator, in: British Machine Vision Conference (BMVC), vol. II, 2003, pp. 549–558.

4. M. Ruzon, C. Tomasi, Color edge detection with the compass operator, in: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 1999, pp. 160–166.

5. A computational approach to edge detection;Canny;IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI),1986

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1. Occlusions are Fleeting - Texture is Forever: Moving Past Brightness Constancy;2017 IEEE Winter Conference on Applications of Computer Vision (WACV);2017-03

2. Collaborative Annotation of Videos Relying on Weak Consistency;ACM Transactions on Multimedia Computing, Communications, and Applications;2016-06-15

3. Event Recognition—Biological;Visual Perception from a Computer Graphics Perspective;2016-04-19

4. A Real-time Object Detection System Using Selected Principal Components;Lecture Notes in Electrical Engineering;2013

5. Recognition of occluded objects by reducing feature interactions;Image and Vision Computing;2012-11

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