18 January 2010 Real-time object detection and tracking in video sequences
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Abstract
One of the most important problems in Computer Vision is the computation of the 2D projective transformation (homography) that maps features of planar objects in different images and videos. This computation is required by many applications such as image mosaicking, image registration, and augmented reality. The real-time performance imposes constraints on the methods used. In this paper, we address the real-time detection and tracking of planar objects in a video sequence where the object of interest is given by a reference image template. Most existing approaches for homography estimation are based on two steps: feature extraction (first step) followed by a combinatorial optimization method (second step) to match features between the reference template and the scene frame. This paper has two main contributions. First, for the detection part, we propose a feature point classification which is applied prior to performing the matching step in the process of homography calculation. Second, for the tracking part, we propose a fast method for the computation of the homography that is based on the transferred object features and their associated local rawbrightness. The advantage of this proposed scheme is a fast and accurate estimation of the homography.
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Fadi Dornaika, Fadi Chakik, "Real-time object detection and tracking in video sequences", Proc. SPIE 7539, Intelligent Robots and Computer Vision XXVII: Algorithms and Techniques, 75390G (18 January 2010); doi: 10.1117/12.838820; https://doi.org/10.1117/12.838820
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