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Computer Vision – ECCV 2014: 13th European Conference, by David Fleet, Tomas Pajdla, Bernt Schiele, Tinne Tuytelaars PDF

By David Fleet, Tomas Pajdla, Bernt Schiele, Tinne Tuytelaars

ISBN-10: 3319105892

ISBN-13: 9783319105895

ISBN-10: 3319105906

ISBN-13: 9783319105901

The seven-volume set comprising LNCS volumes 8689-8695 constitutes the refereed lawsuits of the thirteenth eu convention on desktop imaginative and prescient, ECCV 2014, held in Zurich, Switzerland, in September 2014.
The 363 revised papers provided have been conscientiously reviewed and chosen from 1444 submissions. The papers are prepared in topical sections on monitoring and job popularity; reputation; studying and inference; constitution from movement and have matching; computational images and low-level imaginative and prescient; imaginative and prescient; segmentation and saliency; context and 3D scenes; movement and 3D scene research; and poster sessions.

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Read or Download Computer Vision – ECCV 2014: 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part I PDF

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Get Computer Vision – ECCV 2014: 13th European Conference, PDF

The seven-volume set comprising LNCS volumes 8689-8695 constitutes the refereed complaints of the thirteenth eu convention on computing device imaginative and prescient, ECCV 2014, held in Zurich, Switzerland, in September 2014. The 363 revised papers provided have been conscientiously reviewed and chosen from 1444 submissions. The papers are equipped in topical sections on monitoring and task popularity; reputation; studying and inference; constitution from movement and have matching; computational images and low-level imaginative and prescient; imaginative and prescient; segmentation and saliency; context and 3D scenes; movement and 3D scene research; and poster classes.

Extra resources for Computer Vision – ECCV 2014: 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part I

Sample text

Similar to [5], which treats spatial locations as graph vertices, we build a directed acyclic graph G = (V, E) on the locations and orientations, where the vertices V = {vkt } represent pairs of orientation angles and locations at each time instant, and the edges E = {etkj } represent allowable transitions between them. More specifically, an edge etkj ∈ E connects vertices vkt and vjt+1 if and only if j ∈ N (k). )| O L T , respectively. Recall that we are dealing with two kinds of objects, one of which can contain the other.

These two Visual Tracking by Sampling Tree-Structured Graphical Models                           11        (a) Tree obtained from the key frames in sunshade sequence. Two main subtrees maintain bright and dark sides of face appearances.                    (b) Tree obtained from the key frames in campus sequence. Frames with occlusion are near leaf nodes, which minimizes error propagation.

A global geometric framework for nonlinear dimensionality reduction. Science 290 (2000) 21. : Personalized video summarization with human in the loop. In: WACV (2011) 22. : Semisupervised alignment of manifolds. In: 10th International Workshop on Artificial Intelligence and Statistics (2005) 23. : Learning occlusion with likelihoods for visual tracking. In: ICCV (2011) 24. : Online object tracking: A benchmark. In: CVPR (2013) 16 S. Hong and B. Han 25. : Robust tracking using local sparse appearance model and k-selection.

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Computer Vision – ECCV 2014: 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part I by David Fleet, Tomas Pajdla, Bernt Schiele, Tinne Tuytelaars


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