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Survey of The Problem of Object Detection In Real Images
Dilip K. Prasad
Pages - 441 - 466     |    Revised - 15-11-2012     |    Published - 31-12-2012
Volume - 6   Issue - 6    |    Publication Date - December 2012  Table of Contents
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KEYWORDS
Boosting, Object Detection, Machine learning, Survey.
ABSTRACT
Object detection and recognition are important problems in computer vision. Since these problems are meta-heuristic, despite a lot of research, practically usable, intelligent, real-time, and dynamic object detection/recognition methods are still unavailable. The accuracy level of any algorithm or even Google glass project is below 16% for over 22,000 object categories. With this accuracy, it’s practically unusable. This paper reviews the various aspects of object detection and the challenges involved. The aspects addressed are feature types, learning model, object templates, matching schemes, and boosting methods. Most current research works are highlighted and discussed. Decision making tips are included with extensive discussion of the merits and demerits of each scheme.
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Dr. Dilip K. Prasad
Nanyang Technological University - Singapore
dilipprasad@gmail.com