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Within a surveillance video, occlusions are commonplace, and accurately resolving these occlusions is key when seeking to accurately track objects. The challenge of accurately segmenting objects is further complicated by the fact that within many real-world surveillance environments, the objects appear very similar. For example, footage of pedestrians in a city environment will consist of many people...
Crowd density estimation is important in crowd analysis, this paper proposes a new approach used for crowd density estimation. First, background is removed by using a combination of optical flow and background subtract methods. Then according to texture analysis, a set of new feature is extracted from foreground image. Finally, a self-organizing map neural network is used for classifying different...
The research purpose of this paper is to build a platform for image processing, which can be used to minimize and intelligentize the video image processing system, and make it applicable in various and complicated situations. During the design, related data in broad area has been searched, video processing systems of various engineering vehicles are used as reference, the merits and demerits of different...
In this paper we propose multiple cameras using real time tracking for surveillance and security system. It is extensively used in the research field of computer vision applications, like that video surveillance, authentication systems, robotics, pre-stage of MPEG4 image compression and user inter faces by gestures. The key components of tracking for surveillance system are extracting the feature,...
In this paper a method of real-time target recognition is proposed. When the target is moving, the features of the target are changed. So the features for BP neural network training were obtained according to the moving direction and the target's position in the video Scene. And the recognition results of the previous frames were also considered to get the result of the current frame. The experiments...
Video surveillance systems are commonly used by security personnel to monitor and record activity in buildings, public gatherings, busy roads, and parking lots. These systems allow many cameras to be observed by a small number of trained human operators but suffer from potential operator fatigue and lack of attention due to the large amount of information provided by cameras which can distract the...
Super-resolution is very important in recognizing suspects face in video surveillance system. In this paper, we present an improvement of image super-resolution based on sparse signal representation. The issue of how to deal efficiently with sparse feature has great significance on the quality improvement of generated high resolution image. We propose to use Elastic net to solve sparse representation...
The vehicle shadow's detection and elimination work basically for extracting and tracking the vehicle characteristics, and it also plays a very important role in highway video surveillance and incident detection, affecting the post-processing of video image directly, such as vehicle tracking and speed measurement. On study of Kimmel variational and multi-scale Retinex algorithm to eliminate the vehicle...
In this paper, we propose a macro-observation scheme for unusual event detection in daily life, where motions in time-space domain are described by a global representation and individual activities do not have to be defined and modeled beforehand. The proposed representation records the time-space energy of motions of all moving objects in a scene without segmenting individual object parts or tracking...
Traditional background subtraction methods perform poorly at night. In this paper, a robust method is proposed for automatic visual surveillance in low-light level environment which has quality problems of low brightness, low contrast and high-level noise. The novel method includes techniques of illumination compensation and illumination-invariant background subtraction to solve the low-quality problem...
In this paper, we focus on the visual features of steam injection and propose an integrated algorithm to detect it based on video surveillance. The proposed method is depended on three decision rules which are the attribute of gray level and the feature of frequent flicker rate of steam injection, and the similarity structure between background image and current frame. The block-based approach is...
This paper presents a novel framework for activities perception in video surveillance scenarios. Firstly, moving objects are detected by modeling the background using Gaussian Mixture Model (GMM). Secondly, a novel adaptive particle filter (APF) is introduced. The proposed APF has time-varying dimensions and can track multiple moving objects entering or leaving the field of view effectively. Finally,...
With the rapid development of computer vision and intelligent recognition, real-time alarm analysis of surveillance system has become possible. In this paper, a system for the detection of object entering into prohibited area in surveillance video is designed based on the moving object detection and tracking technology. For motion detection, the Gaussian Mixture Model with background segmentation...
Human visual system function is non-uniform to visual perception. Normally, people tend to focus on one or more specific moving objects while watching video. In addition, video transmission is flawed due to heterogeneous networks and limited bandwidth. Therefore, how to transmit the content of interests more efficiently becomes a growing concerning topic. This paper proposes a method of multi-region...
The proposed technique addresses a fusion method of two imaging sensors on pixel-level. The fused image will provide a scene representation which is robust against illumination changes and different weather conditions. Thus, the combination of the advantages of each camera will extend the capabilities for many computer vision applications, such as video surveillance and automatic object recognition...
This paper proposed an accurate shadow removal method for vehicle tracking. Firstly we detect and remove the shadow using optical gain based gradient analysis,in this process some parts of vehicle which are similar to shadow region in color space may be detected as shadow and removing these parts will leave some holes in the vehicle region. Then we fill these holes using the skeleton information of...
Background reconstruction is very important in many video-based tracking systems. The principle difficulties are the quality and velocity of reconstruction. To cope with these problems, a novel method is proposed. Firstly, the sequence images are decomposed into low frequency sub-images using DWT (discrete wavelet transform). Then, the improved grayscale classification is introduced to reconstruct...
Multi-camera systems are used in many domains such as vision-based robotics or video surveillance. An accurate extrinsic calibration is usually required. In most of cases, this task is done by matching features through different views of the same scene. However, if the cameras' fields of view do not overlap, such a matching procedure is not feasible anymore. Despite this constraint, this article deals...
This paper presents an improved human detection algorithm of motion images. Differences of the two successive frames and background were calculated, then the multiplication of the two differences was obtained; from these results; we can separate the motion human object from the background image and get a motion template which included the motion information. It improved the result of human motion...
In this paper, a surveillance system which provides the protection for property in public places is proposed. Firstly, aiming at the problem of small visual field, Omni-Directional Vision Sensors (ODVS) which has 360 degree and non-dead-angle view is used to capture panoramic images of scene. Secondly, two backgrounds are constructed for detecting a temporarily stationary object, which one is short-term...
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