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We introduce PBG-Net, an object detection system based on an elaborately designed multi-feature deep CNN which works without proposal algorithms. Firstly, PBG-Net aggregates hierarchical features into multi-feature maps and discretizes the output of Conv5 feature map into a set of predicting boxes, namely Predicting Boxes Generation (PBG). Then, PBG-Net crops multi-feature maps via mapping the predicting...
We propose an object detection system that depends on position-sensitive grid feature maps. State-of-the-art object detection networks rely on convolutional neural networks pre-trained on a large auxiliary data set (e.g., ILSVRC 2012) designed for an image-level classification task. The image-level classification task favors translation invariance, while the object detection task needs localization...
Background subtraction is an effective method in detecting moving objects in a static scene, which requires a fixed camera, and a static background. Illumination changing is a challenging problem which causes failure of background subtraction. Most background subtract algorithms require the illumination changing slowly, so the object can be tracked accurately and the background is easy to update....
Object tracking with occlusion handling is a challenging problem in intelligent video surveillance system. Among various tracking algorithms, particle filter (PF) is a robust and accurate one for different applications. In this paper, a new approach based on particle filter is presented for tracking object accurately and steadily when the target encountering occlusion in video sequences. First, the...
This paper proposed a new 2-dimension-code-like feature based on the Haar-like feature proposed by Viola et al. The feature can be calculated in different scales rapidly once the integral image is calculated and this characteristic is inherited from the Haar-like feature. Instead of reducing the dimensions after calculating redundant features, we calculate feature vectors with fixed dimensions for...
Robust and reliable traffic surveillance system is an urgent need to improve traffic control and management. Vehicle flow detection appears to be an important part in surveillance system. The traffic flow shows the traffic state in fixed time interval and helps to manage and control especially when there's a traffic jam. In this paper, we propose a traffic surveillance system for vehicle detection...
Background subtraction is an effective method in detecting moving objects in a static scene, which requires a fixed camera, and a static background. Illumination changing is a challenging problem which causes failure of background subtraction. Most background subtract algorithms require the illumination changing slowly, so the object can be tracked accurately and the background is easy to update....
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