Segmentation of semantic Video Object Planes (VOP's) from video sequence is a key to the standard MPEG-4 with content-based video coding. In this paper, the approach of automatic Segmentation of VOP's Based on...Segmentation of semantic Video Object Planes (VOP's) from video sequence is a key to the standard MPEG-4 with content-based video coding. In this paper, the approach of automatic Segmentation of VOP's Based on Spatio-Temporal Information (SBSTI) is proposed.The proceeding results demonstrate the good performance of the algorithm.展开更多
In order to high reality and efficiency, the technique computer animation. With the development of motion capture, a of motion capture (MoCap) has been widely used in the field of large amount of motion capture data...In order to high reality and efficiency, the technique computer animation. With the development of motion capture, a of motion capture (MoCap) has been widely used in the field of large amount of motion capture databases are available and this is significant for the reuse of motion data. But due to the high degree of freedoms and high capture frequency, the dimension of the mo- tion capture data is usually very high and this will lead to a low efficiency in data processing. So how to process the high dimension data and design an efficient and effective retrieval approach has become a challenge which we can't ignore. In this paper, first we lay out some problems about the key techniques in motion capture data processing. Then the existing approaches are analyzed and sum- marized. At last, some future work is proposed.展开更多
文摘Segmentation of semantic Video Object Planes (VOP's) from video sequence is a key to the standard MPEG-4 with content-based video coding. In this paper, the approach of automatic Segmentation of VOP's Based on Spatio-Temporal Information (SBSTI) is proposed.The proceeding results demonstrate the good performance of the algorithm.
基金Supported by the National Natural Science Foundation of China(No.60875046)by Program for Changjiang Scholars and Innovative Research Team in University(No.IRT1109)+5 种基金the Key Project of Chinese Ministry of Education(No.209029)the Program for Liaoning Excellent Talents in University(No.LR201003)the Program for Liaoning Science and Technology Research in University(No.LS2010008,2009S008,2009S009,LS2010179)the Program for Liaoning Innovative Research Team in University(Nos.2009T005,LT2010005,LT2011018)Natural Science Foundation of Liaoning Province(201102008)by"Liaoning BaiQianWan Talents Program(2010921010,2011921009)"
文摘In order to high reality and efficiency, the technique computer animation. With the development of motion capture, a of motion capture (MoCap) has been widely used in the field of large amount of motion capture databases are available and this is significant for the reuse of motion data. But due to the high degree of freedoms and high capture frequency, the dimension of the mo- tion capture data is usually very high and this will lead to a low efficiency in data processing. So how to process the high dimension data and design an efficient and effective retrieval approach has become a challenge which we can't ignore. In this paper, first we lay out some problems about the key techniques in motion capture data processing. Then the existing approaches are analyzed and sum- marized. At last, some future work is proposed.