TRECVID 2007 High-Level Feature Extraction By MCG-ICT-CAS *

Abstract

For TRECVID 2008 concept detection task, we principally focus on: (1) Early fusion of texture, edge and color features TECM, abbreviation of the combined TF*IDF weights based on SIFT features, Edge Histogram, and Color Moments. (2) To improve the training efficiency and explore the knowledge between concepts or hidden sub-domains more easily and efficiently, we propose a novel method based on Latent Dirichlet Allocation (LDA): LDA-based multiple-SVM (LDASVM). We first use LDA to cluster all the keyframes into topics according to the maximum element of the topic-simplex representation vector (TRV) of each keyframe. Then, we train the annotated data in each topic for each concept. During training,