Intelligent tracking system based on video recording problem is a key technique in computer vision and research focus, a lot of engineering applications and video tracking technology has a close relationship. This sys...
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ISBN:
(纸本)9783037851494
Intelligent tracking system based on video recording problem is a key technique in computer vision and research focus, a lot of engineering applications and video tracking technology has a close relationship. This system is a development platform for the ADSP-BF533 core, together with the VisualDSP + + integrated development and debugging environment, implementation, and optimization meanshift tracking algorithm to achieve real-time tracking of moving target shooting can be used in sporting events, intelligent monitoring. Test data show that the system can control the PTZ camera tracking rigid and non-rigid shooting targeting.
For reducing noise and preferably keeping the edge of image, the mean shift algorithm based on the HIS space is proposed. Firstly the image is changed from RGB space to HIS space. Because the correlation of HIS is ver...
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ISBN:
(纸本)9781424408177
For reducing noise and preferably keeping the edge of image, the mean shift algorithm based on the HIS space is proposed. Firstly the image is changed from RGB space to HIS space. Because the correlation of HIS is very little, H,I and S separately is smoothed based on the different step sizes. Finally the smoothed image is gotten by transforming the HIS space into the RGB space. Because the correlation of the RGB space is more strong, the drawback of the image which could not be separately smoothed by R, G and B is overcomed. The convergence of the moving dot is strictly proved. We prove that the algorithm could get better result than wiener filtering and the mean-shift based on RGB space by experiment.
Human objects Segmentation is one of key problems of visual analysis. In this paper, a novel touched human objects segmentation based on mean shift algorithm is proposed. At first, Video images is preprocessed and for...
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ISBN:
(纸本)9780769534985
Human objects Segmentation is one of key problems of visual analysis. In this paper, a novel touched human objects segmentation based on mean shift algorithm is proposed. At first, Video images is preprocessed and foreground objects (BLOB) is obtained, model of human object is built according to statistical characteristics of body surface. Then, a few of points picked equably from BLOB is taken as seeds, and local mode centroids were calculated by mean-shift iterative process. At last, number of categories is automatic acquisition based on clustering algorithm, and human objects is segmentation according to result of clustering. The experiment based on PETS 2006 Database prove this method is feasible and precisely.
Object detection in videos involves verifying the presence of an object in image sequences and possibly locating it precisely for recognition. Object tracking is to monitor an object's spatial and temporal changes...
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ISBN:
(纸本)9789898111692
Object detection in videos involves verifying the presence of an object in image sequences and possibly locating it precisely for recognition. Object tracking is to monitor an object's spatial and temporal changes during a video sequence, including its presence, position, size, shape, etc. These two processes are closely related because tracking usually starts with detecting objects, while detecting an object repeatedly in subsequent image sequence is often necessary to help and verify tracking. In this paper, a novel approach is being presented for detecting and tracking object. It includes combination of Kalman filter and fast mean shift algorithm. Kalman prediction is measurement follower. It may be misled by wrong measurement. In order to cater it, fast mean shift algorithm is used. It is used to locate densities extrema, which gives clue that whether Kalman prediction is right or it is misled by wrong measurement. In case of wrong prediction, it is corrected with the help of densities extrema in the scene. The proposed approach has the robust ability to track the moving object in the consecutive frames under some kinds of difficulties such as rapid appearance changes caused by image noise, illumination changes, and cluttered background.
Object tracking is a primary step for image processing applications like object recognition, navigation systems and surveillance systems. The current image and the background image is differentiated by approaching con...
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ISBN:
(纸本)9781479939145
Object tracking is a primary step for image processing applications like object recognition, navigation systems and surveillance systems. The current image and the background image is differentiated by approaching conventionally in image processing. Image subtraction based algorithms are mainly used in extracting features of moving objects and take the information in frames. Here three algorithms namely Extended Kalman Filter, Gaussian Mixture Model (GMM), mean shift algorithm are compared in the context of multiple object tracking. The comparative results show that GMM performs well when there are occlusions. Extended Kalman filter fails because of abnormal behavior in the distribution of random variables when there is nonlinear transformation. It cannot identify multiple objects when there are occlusions. mean shift algorithm is best suitable for single object tracking and is very sensitive to window size which is adaptive. Results show that this algorithm has the limitation to detect multiple objects when there is even slight occlusion.
mean shift algorithm has been used in human face tracking during past years and exhibited robust performance compared with other methods. However the existed meanshift methods usually track faces with vertical orient...
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ISBN:
(纸本)9780780397361
mean shift algorithm has been used in human face tracking during past years and exhibited robust performance compared with other methods. However the existed meanshift methods usually track faces with vertical orientation and the tracking effect is deteriorated when the facial orientation changed. In addition, it often adopts the color histogram in RGB color space, which is sensitive to lighting variations. In this paper, we present an adaptive facial orientation template for face tracking in YCb Cr color space and the experimental results show that the tracking is more efficient to adapt the facial orientation and lighting variations than current methods.
mean shift algorithm is recently widely used in tracking clustering, etc, however convergence of mean shift algorithm has not been rigorously proved. In this paper mean shift algorithm with Gaussian profile is studied...
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mean shift algorithm is recently widely used in tracking clustering, etc, however convergence of mean shift algorithm has not been rigorously proved. In this paper mean shift algorithm with Gaussian profile is studied and applied to tracking of objects. The imprecise proofs about convergence of meanshift are firstly pointed out. Then a convergence theorem and its rigorous convergence proof are *** tracking approach of objects based on meanshift is modified. The results of experiment show the modified approach has good performance of object tracking applied to occlusion. The contributions in this paper are expected to further study and application in mean shift algorithm.
Based on the basic principle of mean shift algorithm, this paper proposes an improved target detection and tracking method based on mixture gauss model and mean shift algorithm, aiming at the complex background proble...
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Based on the basic principle of mean shift algorithm, this paper proposes an improved target detection and tracking method based on mixture gauss model and mean shift algorithm, aiming at the complex background problems such as occlusion, shadow, illumination change, etc. The method uses the color feature in YCbCr color space as the target feature, uses the weighted operation of background and target to eliminate the interference of environmental noise, and highlights the effective information of the target itself. In the process of tracking, the target template is constantly updated to keep as consistent as possible with the target state, so as to achieve accurate, real-time and stable tracking of the target in the video stream. The experimental results show that the improved algorithm can effectively reduce the number of iterations and has a good tracking effect.
In this research, we have measured the physical distance between the robot and its surroundings using a laser distance measuring device that we have developed, designed controllers for, and tested operationally. We wi...
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In this research, we have measured the physical distance between the robot and its surroundings using a laser distance measuring device that we have developed, designed controllers for, and tested operationally. We will record the distance using the USB camera and integrate the LDMSB board into the laser distance measuring design. We will fasten these two parts to the robot's underside. Developing the experiment in LabVIEW is the next step. The meanshift method enables us to move the robot's position by relocating a laser-based distance measurement device and capturing a photo at that location. In order to record that area, we will perform a perspective camera calibration. This will allow us to set up or adjust the camera system's value, or provide visual assistance to ensure that the viewing angle is precisely aligned with the intended view angle. The laser measurement results ranged from one to fifteen meters. A device that makes use of lasers has 99.25% accuracy. Every calibration location throughout the 10 has a precision rating of 94.03%.
Eye state analysis in real-time is a main input source for Fatigue Detection Systems and Human Computer Interaction applications. This paper presents a novel eye state analysis design aimed for human fatigue evaluatio...
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Eye state analysis in real-time is a main input source for Fatigue Detection Systems and Human Computer Interaction applications. This paper presents a novel eye state analysis design aimed for human fatigue evaluation systems. The design is based on an interdependence and adaptive scale meanshift (IASMS) algorithm. IASMS uses moment features to track and estimate the iris area in order to quantify the state of the eye. The proposed system is shown to substantially improve non-rigid eye tracking performance, robustness and reliability. For evaluating the design performance an established eye blink database for blink frequency analysis was used. The design performance was further assessed using the newly formed Strathclyde Facial Fatigue (SFF) video footage database(1) of controlled sleep-deprived volunteers. (C) 2014 Elsevier Ltd. All rights reserved.
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