FudaSys Video Retrieval in TRECVID 2012
نویسنده
چکیده
The video retrieval system we developed for TRECVID 2012 mainly involves the semantic indexing task which includes key frame extraction, low level feature extraction, classification and concept fusion. We extracted a new low level feature, explored various classification and fusion schemes. Four “light” runs and two 2 “pair” runs we submitted are as follows: L_A_FudaSys1: Fusion based on concept ontology. L_A_FudaSys2: Weighted fusion of SVM and KNN outputs. L_A_FudaSys3: Average fusion of KNN results. L_A_FudaSys4: Average fusion of SVM outputs. P_A_FudaSys1: Weighted fusion of KNN and SVM Outputs. P_A_FudaSys2: Concept relation fusion of KNN and SVM outcomes. In our experiments, we also implemented various special detectors to detect screen text, black screen and human face to enhance system performance.
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