Keyframe selection for motion capture using motion activity analysis

Motion capture data acquired from high definition cameras creates accurate human motion representation but introduces many redundant frames which pose a problem in data storage and motion retrieval purposes. In this paper, a keyframing approach is proposed to reduce the motion data by extracting key...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلفون الرئيسيون: Kim, Ming-Hwa, Chau, Lap-Pui, Siu, Wan-Chi
مؤلفون آخرون: School of Electrical and Electronic Engineering
التنسيق: Conference or Workshop Item
اللغة:English
منشور في: 2013
الموضوعات:
الوصول للمادة أونلاين:https://hdl.handle.net/10356/102845
http://hdl.handle.net/10220/16918
الوسوم: إضافة وسم
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المؤسسة: Nanyang Technological University
اللغة: English
الوصف
الملخص:Motion capture data acquired from high definition cameras creates accurate human motion representation but introduces many redundant frames which pose a problem in data storage and motion retrieval purposes. In this paper, a keyframing approach is proposed to reduce the motion data by extracting keyframes using motion analysis approach in sampling windows. Motion changes in sampling windows for original motion without frame skipping and with frame skipping are computed. The difference in the motion changes is the main aspect in deciding whether the frames in sampling windows are possible candidates for keyframe selection. Simulation results showed that the proposed method is able to achieve an overall good visual quality for different types of motion. It also gives an improvement of up to 52% in terms of mean square error measurement, as compared to the existing keyframe extraction method, which is curve simplification method.