Volume 13, Issue 3 (12-2016)
JSDP 2016, 13(3): 79-98 |
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hanifelou Z, Monadjemi A H, moallem P. Robust method of changes of light to detect and track vehicles in traffic scenes. JSDP 2016; 13 (3) :79-98
URL: http://jsdp.rcisp.ac.ir/article-1-510-en.html
URL: http://jsdp.rcisp.ac.ir/article-1-510-en.html
faculty of computer engineering, university of isfahan
Abstract: (5813 Views)
In this paper, according to the detection and tracking of the moving vehicles at junctions, a rapid method is proposed which is based on intelligent image processing. In the detection part, the Gaussian mixture model has been used to obtain the moving parts. Then, the targets have been detected using HOG features extracted from training images, Ada-boost Cascade Classifier and the trained SVM. At the tracking part, a number of key points on the image of the vehicle were identified at first. The center of mass of the object and the edges were used to obtain these key points because these points are primarily important and more common in tracking rigid bodies. Then, these points were tracked in consecutive frames using definitive adaptive procedures. Also, the Kalman filter has been used to estimate new locations when the detector is not able to detect the targets. The major advantage of this method in comparison with the previous methods is its resistance against vehicle's overlapping and changes in Illuminations, so that the detection accuracy is 90.80% on overloaded traffic scenes and 88.75% on the tracking vehicles.
Keywords: Detection, Tracking, Ada-boost, Kalman Filter, Vehicle tracking, Deterministic Methods Corresponding, Cost Function
Type of Study: Research |
Subject:
Paper
Received: 2016/05/3 | Accepted: 2016/07/27 | Published: 2017/04/23 | ePublished: 2017/04/23
Received: 2016/05/3 | Accepted: 2016/07/27 | Published: 2017/04/23 | ePublished: 2017/04/23
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