TY - GEN
T1 - Video clip retrieval by maximal matching and optimal matching in graph theory
AU - Peng, Yu-Xin
AU - Ngo, Chong-Wah
AU - Dong, Qing-Jie
AU - Guo, Zong-Ming
AU - Xiao, Jian-Guo
PY - 2003
Y1 - 2003
N2 - In this paper, a novel approach for automatic matching, ranking and retrieval of video clips is proposed. Motivated by the maximal and optimal matching theories in graph analysis, a new similarity measure of video clips is defined based on the representation and modeling of bipartite graph. Four different factors: visual similarity, granularity, interference and temporal order of shots are taken into consideration for similarity ranking. These factors are progressively analyzed in the proposed approach. Maximal matching utilizes the granularity factor to efficiently filter false matches, while optimal matching takes into account the visual, granularity and interference factors for similarity measure. Dynamic programming is also formulated to quantitatively evaluate the temporal order of shots. The final similarity measure is based on the results of optimal matching and dynamic programming. Experimental results indicate that the proposed approach is effective and efficient in retrieving and ranking similar video clips.
AB - In this paper, a novel approach for automatic matching, ranking and retrieval of video clips is proposed. Motivated by the maximal and optimal matching theories in graph analysis, a new similarity measure of video clips is defined based on the representation and modeling of bipartite graph. Four different factors: visual similarity, granularity, interference and temporal order of shots are taken into consideration for similarity ranking. These factors are progressively analyzed in the proposed approach. Maximal matching utilizes the granularity factor to efficiently filter false matches, while optimal matching takes into account the visual, granularity and interference factors for similarity measure. Dynamic programming is also formulated to quantitatively evaluate the temporal order of shots. The final similarity measure is based on the results of optimal matching and dynamic programming. Experimental results indicate that the proposed approach is effective and efficient in retrieving and ranking similar video clips.
UR - http://www.scopus.com/inward/record.url?scp=10044255867&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-10044255867&origin=recordpage
U2 - 10.1109/ICME.2003.1220918
DO - 10.1109/ICME.2003.1220918
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 780379659
VL - 1
SP - I317-I320
BT - Proceedings - IEEE International Conference on Multimedia and Expo
PB - IEEE Computer Society
T2 - 2003 International Conference on Multimedia and Expo, ICME 2003
Y2 - 6 July 2003 through 9 July 2003
ER -