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Matching observations captured by pedestrian detectors across the cameras with non-overlapping views, known as person re-identification, is challenging due to the appearance changes caused by pose, viewpoint and illumination variations, occlusions and cluttered background. Different from various hand-crafted features, this paper extract the features through the fine-tuned deep convolutional neural...
This paper presents a fuzzy-based intelligent control strategy allowing a mobile robot to safely follow a given person. The robot is embedded with two sensors: a RFID and a stereo camera. The RFID can locate the given person with an ID tag, and the stereo camera can be used to detect the target. Based on the two sensors, a robust control strategy is designed according to the target's speed and his...
This paper presents a person detection and tracking method for a mobile robot by fusing the data from Radio Frequency Identification (RFID) and stereo camera. The RFID system detects a person wearing an ID tag and a course position estimate of the person is obtained. The stereo camera is used for person detection based on the compressive sensing theory. Less Haar-like features are extracted from compressed...
In this paper, we propose a system using video cameras to perform vehicle identification. We tackle this problem by reconstructing an input by using multiple linear regression models and compressed sensing, which provide new ways to deal with three crucial issues in vehicle identification, namely, feature extraction, online vehicle identification database buildup , and robustness to occlusions and...
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