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Automated detection and recognition of human abnormal behavior is the key problem of monitoring systems. We construct a complete system that is able to alert the human operator when a knife in hand is visible in camera views. We use RealSense 3D camera to track hands, modified MPEG-7 EHD as feature vector and none-linear SVM as classifier. In this paper, we improve the feature extraction algorithm...
This paper proposed a new pedestrian detection method with depth information based on Histogram of Oriented Gradient and Support Vector Machin. According to the principle of perspective, use the different classifier with different scale in different position of the image to reduce the detection time. At the same time, Adding the Hard Examples to negative sample to decrease the false positive rate...
This paper addresses view-invariant object detection and pose estimation from a single image. While recent work focuses on object-centered representations of point-based object features, we revisit the viewer-centered framework, and use image contours as basic features. Given training examples of arbitrary views of an object, we learn a sparse object model in terms of a few view-dependent shape templates...
In this paper we explore how a structured light depth sensor, in the form of the Microsoft Kinect, can assist with indoor scene segmentation. We use a CRF-based model to evaluate a range of different representations for depth information and propose a novel prior on 3D location. We introduce a new and challenging indoor scene dataset, complete with accurate depth maps and dense label coverage. Evaluating...
We present a real-time distributed system for tracking with non-overlapping camera views. Each camera performs multi-object tracking, and cameras communicate with each other in a peer-to-peer manner for consistent labeling. To match objects across non-overlapping views, we employ multiple features, namely color histogram, height, travel time and speed. First, camera configuration and reference values...
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