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Object Tracking by Maximizing Classification Score of Detector Based on Rectangle Features
Akinori HIDAKA Kenji NISHIDA Takio KURITA
IEICE TRANSACTIONS on Information and Systems
Publication Date: 2008/08/01
Online ISSN: 1745-1361
Print ISSN: 0916-8532
Type of Manuscript: PAPER
Category: Image Recognition, Computer Vision
object detection, tracking, support vector tracker, rectangle features, boosting,
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In this paper, we propose a novel classifier-based object tracker. Our tracker is the combination of Rectangle Feature (RF) based detector , and optical-flow based tracking method . We show that the gradient of extended RFs can be calculated rapidly by using Integral Image method. The proposed tracker was tested on real video sequences. We applied our tracker for face tracking and car tracking experiments. Our tracker worked over 100 fps while maintaining comparable accuracy to RF based detector. Our tracking routine that does not contain image I/O processing can be performed about 500 to 2,500 fps with sufficient tracking accuracy.