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Parallel Computing in Face Image Retrieval: Practical Approach to the Real-World Image Search

Parallel Computing in Face Image Retrieval: Practical Approach to the Real-World Image Search
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Author(s): Eugene Borovikov (National Library of Medicine, USA), Szilárd Vajda (National Library of Medicine, USA), Girish Lingappa (National Library of Medicine, USA)and Michael C. Bonifant (National Library of Medicine, USA)
Copyright: 2017
Pages: 35
Source title: Multi-Core Computer Vision and Image Processing for Intelligent Applications
Source Author(s)/Editor(s): Mohan S. (Al Yamamah University, Saudi Arabia)and Vani V. (Al Yamamah University, Saudi Arabia)
DOI: 10.4018/978-1-5225-0889-2.ch006

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Abstract

Modern digital photo collections contain vast multitudes of high-resolution color images, many containing faces, which are desirable to retrieve visually. This poses a problem for effective image browsing and calls for efficient Content Based Image Retrieval (CBIR) capabilities ensuring near-instantaneous visual query turn-around. This in turn necessitates parallelization of many existing image processing and information retrieval algorithms that can no longer satisfy the modern user demands, when executed sequentially. Hence a practical approach to Face Image Retrieval (FIR) is presented. It utilizes multi-core processing architectures to implement its major modules (e.g. face detection and matching) efficiently without sacrificing the image retrieval accuracy. The integration of FIR into a web-based family reunification system demonstrates the practicality of the proposed method. Several accuracy and speed evaluations on real-word data are presented and possible CBIR extensions are discussed.

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