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Titlebook: Computer Analysis of Images and Patterns; 14th International C Pedro Real,Daniel Diaz-Pernil,Walter Kropatsch Conference proceedings 2011 S

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A Homological–Based Description of Subdivided nD Objectswo levels: local and global. Therefore, our method presents several advantages with respect to the existing Algebraic topological models, and techniques based in Discrete Morse Theory. A construction algorithm has been implemented, and some examples are shown.
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Automatic Conic and Line Grouping for Calibration of Central Catadioptric Cameraial lines’ geometric properties under central catadioptric projection, we show that automatic calibration of catadioptric from a single image can be achieved. The experiment results show that the method not only improve the accuracy of the conic fitting in the image but also provide robustness against conic occlusion and noise.
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Multi-cue-Based Crowd Segmentation in Stereo Visionarity values of some foreground blobs, which are calculated concurrently during crowd segmentation. Crowd segmentation is therefore achieved with evidences from both shape and depth cues. The methods were evaluated on two video sequences. The results show that the segmentation performance has been improved when depth cues are considered.
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Error Bounds on the Reconstruction of Binary Images from Low Resolution Scansh the given measurements. We also derive a bound on the difference between any two binary images having these pixel sums. Both bounds are evaluated experimentally for different geometrical settings, based on simulated scan data for a range of images.
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0302-9743 l section on: motion analysis, image and shape models, segmentation and grouping, shape recovery, kernel methods, medical imaging, structural pattern recognition, Biometrics, image and video processing, calibration; and tracking and stereo vision.978-3-642-23671-6978-3-642-23672-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
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https://doi.org/10.1007/978-3-663-08167-8is modular and robust with respect to noise, non-rigid and non-metric-preserving shape transformations. The proposed framework allows us to improve the ability of 2-dimensional size functions in discriminating between shapes.
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,Benutzeroberfläche als Bildraum,ow complexity. Our results suggest that, compared to first-order approaches, it scores similar or better results and usually requires considerably less user-input. As opposed to a recently introduced efficient second-order scheme, both closed contours and open contours with fixed endpoints can be computed with our technique.
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