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

Borovikov E, Vajda S, Lingappa G, Bonifant MC

Multi-Core Computer Vision and Image Processing for Intelligent Applications. IGI Global, 2017. 155-189. Web. 12 Sep. 2016. 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.

Borovikov E, Vajda S, Lingappa G, Bonifant MC. Parallel Computing in Face Image Retrieval: Practical Approach to the Real-World Image Search. 
Multi-Core Computer Vision and Image Processing for Intelligent Applications. IGI Global, 2017. 155-189. Web. 12 Sep. 2016. doi:10.4018/978-1-5225-0889-2.ch006

URL: http://www.igi-global.com/chapter/parallel-computing-in-face-image-retrieval/163730