Modeling Local Interest Points for Semantic Detection and Video Search at TRECVID 2006.
Yu–Gang Jiang, Xiao-Yong Wei, Chong‐Wah Ngo, Hung‐Khoon Tan, Wan‐Lei Zhao, Xiao Ying Wu · 2006
Local interest points (LIPs) and their features have been shown to obtain surprisingly good results in object detection and recognition. Its effectiveness and scalability, however, have not been seriously addressed in large-scale multimedia database, for instance TRECVID benchmark. The goal of our works is to investigate the role and performance of LIPs, when coupling with multi-modality features, for high-level feature extraction and automatic video search. In high-level feature extraction, we explore LIPs with both local description and spatial distribution for characterizing and sketching semantic concepts respectively. Two visual dictionaries,