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This paper proposes an algorithm for detecting bicycles on the road from a sequence of images acquired by a stationary video camera. This algorithm is suitable for monitoring the traffic situation for safety, our algorithm includes shape-based object detection using HOG and SVM and relative motion detection for leg movements in bicycle pedaling. The leg movement, which can be achieved by using spatiotemporal...
In this paper, we propose a Markov random field sequence segmentation and regions tracking model, which aims at combining color, texture, and motion features. First a motion-based segmentation is realized. Namely the global motion of the video sequence is estimated and compensated. From the remaining motion information, a rough motion segmentation is achieved. Then, we use a Markovian approach to...
In the context of automotive driving assistance, this paper describes a generic (i.e. applicable to both vehicle interior and exterior scenes) vision based approach for scene content analysis. It makes use of temporal and spatial information from a stereoscopic sequence of images to localize objects and estimate their position and motion. The proposed method is divided into three steps. First, image...
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