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This paper deals with the video surveillance problem in static camera. The aim is to design a moving object detection system based on advanced CPU DM6437. After capturing the pictures according to the timing, the background model is established without the objects and the background information is real-time updated due to the changes of the environment. After that, background subtraction is used so...
Designing static object detection systems that are able to incorporate user interaction conveys a great benefit in many surveillance applications, since some correctly detected static objects can be considered to have no interest by a human operator. Interactive systems allow the user to include these decisions into the system, making automated surveillance systems more attractive and comfortable...
Background subtraction is widely used for extracting unusual motion of object of interest in video images. In this paper, we propose a fast and flexible approach of object detection based on an adaptive background subtraction technique that also effectively eliminates shadows based on color constancy principle in RGB color space. This approach can be used for both outdoor and indoor environments....
In this paper we implement a vision based moving Object Tracking system with Wireless Surveillance Camera which uses a color image segmentation and color histogram with background subtraction for tracking any objects in non-ideal environment. The implementation of the moving video objects can be based on any one of the tracking algorithms such as Template matching, Continuously Adaptive Mean Shift...
Traditional level-set-based methods of tracking contours suffered from occlusion and fusion. In this paper, the proposed method introduces dynamic incident detection to find and handle occlusion and fusion. Color histogram of the hue component in HSV color space is used to identify the objects re-entering after occlusion. On the other hand, object features including the size and the motion pattern...
In order to detect the location of smoke in the Measuring System for Ground Shell Dispersion (MSGSD), presented an improved algorithm for the Background Subtraction. Focused on introducing design of the image detection algorithm. The results show that the system can quickly, accurately and effectively detect the location of the smoke.
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,...
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 describe a new algorithm focused on obtaining stationary foreground regions, which is useful for applications like the detection of abandoned/stolen objects and parked vehicles. Firstly, a sub-sampling scheme based on background subtraction techniques is implemented to obtain stationary foreground regions. Secondly, some modifications are introduced on this base algorithm with the...
Combing with specific temporal information of video, this paper proposes a kind of video object tracking method based on normalized cross-correlation matching by using the high precision characteristics of normalized cross-correlation image matching. Firstly, extract video background from the temporal information of video. Then, acquire the region of moving object using background subtraction. Lastly,...
This paper proposes a new ego-motion estimation and background/foreground classification method to effectively segment moving objects from videos captured by a moving camera on a moving platform. Existing methods for moving-camera detecting impose serious constraints. In our approach, ellipsoid scene shape is applied in the motion model and a complicated ego-motion estimation formula is derived. Genetic...
This paper describes an embedded system for real-time human motion detection using a fixed camera. A modified version of the Codebook algorithm is developed to detect moving objects. This algorithm provides fast background modelling and subtraction with small storage memory requirements. Then, the system detects humans using a simplified Skeletonization algorithm, which uses the individual human shape...
This paper proposes an obstacle detection system for the purpose of preventing accidents at level crossings. In order to avoid the limits of already proposed technologies, this system uses stereo cameras to detect and localize multiple targets at the level crossing. In a first step, a background subtraction module is performed using the Color Independent Component Analysis (CICA) technique which allows...
In this paper we implement a vision based moving Object Tracking system with Wireless Surveillance Camera which uses a color image segmentation and color histogram with background subtraction for tracking any objects in non-ideal environment. The implementation of the moving video objects based on the Continuously Adaptive Mean Shift (CAMSHIFT) algorithm is presented by optimizing the kernel variants...
In this paper a new approach aimed at automatic identify events of abandoned and stolen objects detection in video surveillance system is described. Our method mainly includes three steps of data processing: the first processing phrase is object extraction, involving a background subtraction algorithm which dynamically updates two sets of background. Then, extracted objects are classified as static...
Identifying moving objects from a video sequence is a fundamental task in many computer-vision applications. Background subtraction is a widely used approach for detecting moving objects from static cameras. However, this approach is very sensitive to scene changes due to changes in lighting and movement of background objects, therefore, it should be carefully modeled to be adaptive to any of those...
Human activity recognition is an active research field in computer vision and image processing. This paper has been concentrated on the recognition between different cyclic motion activities such as running and walking. The proposed system consists of three major steps. Initially by using a single camera, in a variety of angles, the movement of the object is detected, and object silhouette is generated...
Background subtraction is widely used in detecting moving objects in a static scene, which requires a fixed camera, and a static background. Most background subtract algorithms require the illumination changing slowly, so can be tracked and updated. If the illumination changes fast and non-monotony, many algorithms fail. Here we research one scene in changing illumination: multiple continuous varying...
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....
Background subtraction is widely used in detecting moving objects in a static scene, which requires a fixed camera, and a static background. Most background subtract algorithms require the illumination changing slowly, so can be tracked and updated. If the illumination changes fast and non-monotony, many algorithms fail. Here we research one special scene in changing illumination: single continuous...
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