Inference and Retrieval of Facial Images

• Main Authors: WU, Jian Kang, ANG, Yew Hock, LAM, Chiam Prong, LOH, Hean Ho, NARASIMHALU, Arcot Desai
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 1994
• Subjects: Multimedia database system; Iconic index; Visual browsing; Similarity retrieval; Free text retrieval; Fuzzy retrieval; Self-organization neural net index; Computer Sciences; Management Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/11; https://doi.org/10.1007/BF01213579
• Institution: Singapore Management University

Attempts have been made to extend SQL to work with multimedia databases. We are reserved on the representation ability of extended SQL to cope with the richness in content of multimedia data. In this paper we present an example of a multimedia database system, Computer Aided Facial Image Inference and Retrieval system (CAFIIR). The system stores and manages facial images and criminal records, providing necessary functions for crime identification. We would like to demonstrate some core techniques for multimedia database with CAFIIR system. Firstly, CAFIIR is a integrated system. Besides database management, there are image analysis, image composition, image aging, and report generation subsystems, providing means for problem solving. Secondly, the richness of multimedia data urges feature-based database for their management. CAFIIR is feature-based. A indexing mechanism,iconic index, has been proposed for indexing facial images using hierarchical self-organization neural network. The indexing method operates on complex feature measures and provides means for visual navigation. Thirdly, special retrieval methods for facial images have been developed, including visual browsing, similarity retrieval, free text retrieval and fuzzy retrieval.