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It is a challenging task to detect people in crowded scene owing to the heavy occlusion and small object characteristic of crowed people. In this paper we propose a multi-layer regional-based convolutional network to address the tasks of people detection in the crowded scenes. Unlike the traditional methods, we propose an end-to-end framework that uses the convolutional network as feature extractor...
The detection of people in crowded scenes is a challenging task owing to both the severe occlusion among people and various changes in posture. We propose a regional-based convolutional network to address the tasks of people detection in the crowded scenes. Unlike the traditional methods, we propose an end-to-end framework that uses the convolutional network for feature representation, which generates...
Objectness measure, which generates some candidate object proposals, has been shown to accelerate the traditional sliding window category-dependent object detection methods. Binarized Normed Gradients (BING) is one of the state-of-the-art detectors. It achieves high object detection rate (DR), but moderate object overlap rate (OR) because the candidate proposals produced by BING are fixed-sized. In...
This paper presents an improved method for removing cast shadows from multiple objects in a static background using gradient amendment. Shadow can decrease object detection rate and increase the likelihood of tracking failure, which are the two most important measure of algorithm in intelligent video system. The drawback of existed shadow detection methods is the fracture problem of objects, especially...
Focusing on vehicle detection system, multi-vehicles are detected as a single target, disturbed by cast shadows. No matter what illumination, or if there are shadows, the luminance of the vehicle bottom decreased, the area is the darkest region of an image, is an important information for vehicle detection. Our results show the self-adaptive for the illumination variance, and low ratio of miss detection...
Intelligent traffic detection has been paid much attention in many years, and the shadow removal was the key problem in this technique. Usually, geometric characteristics were used for vehicle detection or person detection, but it is not robust to shadow. Shadow in this paper was formed by vehicle's occlusion in the direction of the incident light and we want to remove the part projected in background...
A shadow detection algorithm base on spatial features was proposed, in the case of focusing on traffic vehicle detection system. First of all, multi-foreground rectangles were extracted by using Gaussian mixture model (GMM) and edge detection operator of mathematical morphology. Then, histogram of horizontal location - foreground point number of vertical direction was computed, combined with optimum...
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