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Titlebook: Articulated Motion and Deformable Objects; 8th International Co Francisco José Perales,José Santos-Victor Conference proceedings 2014 Sprin

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期刊全稱(chēng)Articulated Motion and Deformable Objects
期刊簡(jiǎn)稱(chēng)8th International Co
影響因子2023Francisco José Perales,José Santos-Victor
視頻videohttp://file.papertrans.cn/162/161982/161982.mp4
學(xué)科分類(lèi)Lecture Notes in Computer Science
圖書(shū)封面Titlebook: Articulated Motion and Deformable Objects; 8th International Co Francisco José Perales,José Santos-Victor Conference proceedings 2014 Sprin
影響因子This book constitutes the refereed proceedings of the 8th International Conference on Articulated Motion and Deformable Objects, AMDO 2014, held in Palma de Mallorca, Spain, in July 2014. The 18 papers presented were carefully reviewed and selected from 37 submissions. The conference dealt with the following topics: geometric and physical deformable models; motion analysis; articulated models and animation; modeling and visualization of deformable models; deformable model applications; motion analysis applications; single or multiple human motion analysis and synthesis; face modeling, tracking, recovering and recognition models; virtual and augmented reality; haptics devices; biometric techniques.
Pindex Conference proceedings 2014
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3D Human Motion Analysis for Reconstruction and Recognition,e its pose. Third, the entire gait sequence is recovered by interpolation of joint positions in the fitted body models. Representative results have been shown to ensure the robustness of the proposed method.
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Non-rigid Object Segmentation Using Robust Active Shape Models,ectation-Maximization method and the weights are updated in each iteration. The algorithm was tested in ultrasound images of the left ventricle and compared with the output of classic Active Shape Models. The proposed algorithm performs significantly better.
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efficient mode-seeking algorithm. In comparison to other holistic approaches, we can recover body poses from occlusion or noisy data. We demonstrate the power of our method in two publicly available datasets and propose a third one. Finally, we achieve state-of-the-art results in comparison to other approaches.
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