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Erschienen in:
2015 | OriginalPaper | Buchkapitel
Vision-Based Vehicle Counting with High Accuracy for Highways with Perspective View
verfasst von : Mohammad Shokrolah Shirazi, Brendan Morris
Erschienen in: Advances in Visual Computing
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Abstract
Vehicle detection by motion is still a common method used in vision-based tracking systems due to vehicles’ continuous motion on highways. However, counting accuracy is affected for highways with perspective view due to long-time merging (i.e. blob merging or occlusion) events. In this work, a new way of vehicle counting with high accuracy using two appearance-based classifiers is proposed to detect merging situations and handle vehicle counts. Experimental results on three Las Vegas highways with differing perspective views and congestion difficulties show improvement in counting and general applicability of the proposed method. Moreover, tracking and counting results of a highly cluttered highway indicates greater counting improvement (89 % to 94 %) for highly congested situations.