کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
527025 869273 2013 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Simultaneous particle tracking in multi-action motion models with synthesized paths
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Simultaneous particle tracking in multi-action motion models with synthesized paths
چکیده انگلیسی

This paper proposes human motion models of multiple actions for 3D pose tracking. A training pose sequence of each action, such as walking and jogging, is separately recorded by a motion capture system and modeled independently. This independent modeling of action-specific motions allows us 1) to optimize each model in accordance with only its respective motion and 2) to improve the scalability of the models. Unlike existing approaches with similar motion models (e.g. switching dynamical models), our pose tracking method uses the multiple models simultaneously for coping with ambiguous motions. For robust tracking with the multiple models, particle filtering is employed so that particles are distributed simultaneously in the models. Efficient use of the particles can be achieved by locating many particles in the model corresponding to an action that is currently observed. For transferring the particles among the models in quick response to changes in the action, transition paths are synthesized between the different models in order to virtually prepare inter-action motions. Experimental results demonstrate that the proposed models improve accuracy in pose tracking.

Figure optionsDownload high-quality image (148 K)Download as PowerPoint slideHighlights
► We propose the models of human motion prior with multi-actions for pose tracking.
► Each action-specific model is used for tracking in its respective human action.
► The models are connected via synthesized paths for following action transition.
► The transition paths improve tracking accuracy even during action transitions.
► All models are used simultaneously for utilizing multiple hypotheses of actions.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Image and Vision Computing - Volume 31, Issues 6–7, June–July 2013, Pages 448–459
نویسندگان
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