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Independent Object Tracking from Video using the Contour Information in HSV Color Space
Background/Objectives: In this paper, a tracking method that is based on the colors and contours is proposed to obtain results that are superior to those of the traditional methods for the tracking of the objects in video. Methods/Statistical Analysis: The proposed method requires an initial conversion of the existing RGB-color-based video in the HSV color space, and a back-projection histogram in the HSV color space is used to obtain the color information of the object region that is to be tracked. The contour information is also obtained to track the target based on the Canny algorithm, whereby the moving object in the video is tracked in real time on the basis of the color and contour information. Findings: An experiment was performed wherein the proposed method was compared with the Mean-shift tracking method, the Camshaft tracking method, the Kalman-filter tracking method, and the Particle-filter tracking method in terms of the objective of this paper. The comparison showed that the proposed method is more accurate regarding the tracking of a single object in video. Improvements/Applications: This improved tracking method will be utilized in object tracking, CCTV for car tracking and HCI.
Canny Algorithm, Contour Detection, Histogram Back-Projection, Object Tracking, RGB-to-HSV Conversion.
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