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This paper proposes a front object recognition system for the safety of driving, which is based on sensor fusion with laser range finder and stereo vision. The study utilizes a stereo vision system for objects detection. Since the calculation time of the stereo vision algorithm is too long, in order to detect objects immediately, a laser range finder is integrated to improve the calculation time and...
One of the main problems of binary classification of overlapping distributions is that there always exist misclassification errors with any value of threshold. In this paper, we propose a novel lazy decision approach for robust object detection and tracking, where decision on an uncertain observation whose evaluation lies between low and high thresholds is postponed until a clear evidence appears...
In this paper, we proposed a pedestrian detection system based on laser and image data fusion. The high speed of laser data based location and precise of image based classification are fully explored. First, laser scanner point data is clustered into segments, each of which implies a pedestrian candidate. Then, the segments are projected to the image domain to form regions of interest (ROI) on the...
This paper proposes an effective method for extracting corner features on structured environment based on sensor fusion of monocular vision and laser range data during Simultaneous Localization and Mapping (SLAM). Fusing vision and laser data of the same corner feature, not only improving the accuracy of SLAM, but also obtaining more three-dimensional information, which extends a two-dimensional map...
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