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http://dx.doi.org/10.9717/kmms.2020.24.2.305

Estimation of Moving Direction of Objects for Vehicle Tracking in Underground Parking Lot  

Nguyen, Huu Thang (School of Electronic and Electrical Engineering, Hongik Univ.)
Kim, Jaemin (School of Electronic and Electrical Engineering, Hongik Univ.)
Publication Information
Journal of Korea Multimedia Society / v.24, no.2, 2021 , pp. 305-311 More about this Journal
Abstract
One of the highly reliable object tracking methods is to trace objects by associating objects detected by deep learning. The detected object is represented by a rectangular box. The box has information such as location and size. Since the tracker has motion information of the object in addition to the location and size, knowing additional information about the motion of the detected box can increase the reliability of object tracking. In this paper, we present a new method of reliably estimating the moving direction of the detected object in underground parking lot. First, the frame difference image is binarized for detecting motion energy, change due to the object motion. Then, a cumulative binary image is generated that shows how the motion energy changes over time. Next, the moving direction of the detected box is estimated from the accumulated image. We use a new cost function to accurately estimate the direction of movement of the detected box. The proposed method proves its performance through comparative experiments of the existing methods.
Keywords
Moving direction estimation; Detected bounding box; Vehicle tracking; Accumulated binary frame difference image;
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