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In this paper, we present a novel approach for video anomaly detection in crowded scenes. The proposed approach detects anomalies based on the contextual information analysis within spatio-temporal video volume. Around each pixel, spatio-temporal volumes are built and clustered to construct the activity pattern codebook. Then, the composition information of(More)
In this paper we present a method to detect and localize abnormal events in crowded scene. Most existing methods use the patch of optical flow or human tracking based trajectory as representation for crowd motion, which inevitably suffer from noises. Instead, we propose the employment of a new and efficient feature, short-term trajectory, which represent(More)
In this paper, we propose a new approach for anomaly detection in video surveillance. This approach is based on a nonparametric Bayesian regression model built upon Gaussian process priors. It establishes a set of basic vectors describing motion patterns from low-level features via online clustering, and then constructs a Gaussian process regression model(More)
We propose a novel approach for the crowd anomaly detection in multiple cameras with non-overlapping view. In this paper, we refer to the activities of crowd in far-field scenes. Firstly, we present a model for learning all of the motion patterns under single camera view, which are regarded as the normal situation. In the surveillance region, we mark the(More)
In this paper, we present an automatic method to remove shadows in light field images. Taking into account the internal structure of the light field data, depth map of the captured scene is extracted to calculate the surface normal. Using nonlocal matching by combining chromaticity, normal and spatial location information in an anisotropic window, the(More)
In recent years, researchers come up with lots of path following algorithms. One of their basic assumptions is that the robot's initial position is a single certain point. Actually, as robots rely on sensor data to locate by Kalman filter or Partical filter, it outputs a probability distribution. In this paper, F* describes a new path following algorithm(More)
This paper presents a calibration framework for calibrating the pose of two cameras with non-overlapping region with the help of a mobile robot. Firstly, intrinsic parameters are calibrated separately by using camera calibration toolbox for MATLAB. To establish the position relationship between the two fixed cameras, the movement of mobile robot at two(More)
In this paper we present a method to grasp workpiece by the industrial robot arm based on the machine vision. Most existing methods use the kind of camera calibration methods to establish the spatial position relationship of the robot arm and the workpiece in the image. Instead, we propose a new location method, which is based on using the Hermite(More)
This paper presents a method to analyze crowd with computer vision techniques in virtual environments. To overcome the difficulty of obtaining video evidence in hazard situations, or, to meet the demand of big data for machine learning methods, we attempt to use virtual models to simulate actual ones. To prove the reliability of virtual crowd models we(More)