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We present a new framework for driver assistance system, detecting moving objects in the street scene. Our algorithm supports a wide range of objects including vehicles, cyclists, pedestrian etc. Based on candidate bounding boxes detected by object proposals, our classifier only responds to the objects truly moving, which is more practical for real applications. Using unified features of color, structure...
This paper proposes a new approach of abnormal vehicle detection for frontal and lateral collision warnings in nighttime driving using monocular vision. Motion information is used to estimate moving objects. An empirical threshold range is introduced to eliminate efficiently most of non-vehicle regions. Vehicle candidates are segmented by using K-means clustering. An analysis is performed carefully...
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