Modeling local interest points for semantic detection and video search at TRECVID 2006

• Main Authors: JIANG, Yu-Gang, WEI, Xiaoyong, NGO, Chong-wah, TAN, Hung-Khoon, ZHAO, Wanlei, WU, Xiao
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2006
• Subjects: Data Storage Systems; Graphics and Human Computer Interfaces
• Online Access: https://ink.library.smu.edu.sg/sis_research/6642; https://ink.library.smu.edu.sg/context/sis_research/article/7645/viewcontent/Modeling_local_interest_points_for_seman.pdf
• Institution: Singapore Management University

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.