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In order to accurately track sea cucumber on the assembly line to realize automatic grabbing using mechanical arm, an object tracking method based on Mean-shift algorithm was proposed. Firstly, the contours of the objects was extracted from the original image to select tracking target, and then the local image was cropped at the same position and local area in the second frame, and mean-shift algorithm...
Tracking of any given object forms integral part in surveillance, control and analysis applications. The video tracker presented here works on the principle of mean shift. Mean shift is an iterative algorithm which is extended to the field of object tracking. However mean shift tracker losses track of the object when there are variations in illumination. In order to improve the performance of the...
Mean-shift tracking algorithm is a widely-used tool for efficiently tracking target. However, the background change and shade usually lead to tracking errors and low tracking accuracy. In this paper, we introduce a novel mean-shift tracking algorithm based on weighted sub-block which incorporates the improved level set target extraction. The weight of each sub-block is determined by the similarity...
To reduce the tracking errors caused by high-speed motion and variable motion in the process of moving target tracking, a novel Mean-Shift tracking algorithm based on Kalman filter using adaptive window and sub-blocking is proposed in this paper. Moving target's utmost position is predicted by combining Kalman filter and historical information, which is used as the initial position. During describing...
This paper introduces an algorithm to automatically and continuously select the most appropriate color space to use in order to improve the performances of visual tracking. Eight color spaces are tested, and the Mean-Shift (MS) tracker is considered. The selection of the colorspace is made using an evaluation criterion based on the quality of the weights involved in the MS tracking, and implicitly...
The mean-shift algorithm has achieved considerable success in object tracking due to its simplicity and robustness. However, the lack of spatial information often leads to false positives of the color based tracker when the background has a similar color style. Furthermore, the classical similarity measures are not very discriminative. In this paper, an improved mean-shift tracking algorithm with...
In panoramic videos, the object movement between adjacent side images leads to deformation and discontinuity, which makes the traditional video tracking approaches insufficient. An effective static object tracking algorithm is proposed in this paper to resolve the tracking problems from the deformation and discontinuity in cubic panorama. The algorithm extends the relevant side images with boundary...
This paper presents a real-time and automatic video tracking system with a single pan-tilt-zoom (PTZ) camera. Compared with fixed camera, it can enlarge the surveillance area. By using three-dimensional background-weighted histogram in HSV color space, an improved mean-shift algorithm is proposed, and the algorithm can track target with multiple colors in real time. To keep the target in the center...
Mean-shift algorithm is one of the well-known tracking algorithms because of its robust performance. However, Mean-shift algorithm tracks targets only by the color or intensity features. That is to say that, Mean-shift can only tracking the statistical features of pixels. The universal Mean-shift which can track any features of targets has not been developed. We propose a strategy which does not need...
A multi-object tracking algorithm is proposed for road & bridge traffic scene. Firstly, background reconstruction was conducted based on a statistical model, and the background was updated using Kalman filter at regular intervals. Secondly, the background differencing was conducted to obtain potential objects. An improved mean-shift tracking algorithm was put forwarded for image sequences without...
Both color feature and edge feature have been researched in target tracking field, but these two features have been studied separately in target tracking field. Use single feature make the tracking system instability sometimes. In order to enhance robustness of real-time target tracking system under complex conditions such as scenes changes, occlusion and background confusion, this paper use two mutual...
In this paper, we propose a color tracking method mean-shift based on the robust color system. Our proposed color system is simple calculation, and then proposed system can calculate faster than conventional normalized vector distance (NVD). We show validity of proposed method by experimental result that our method enables real-time color object tracking of illuminance changing conditions.
To improve the limitation of Mean-Shift lack of the template update, an algorithm based on mixture Gaussian model is proposed. It treats the target region as ldquobackgroundrdquo, and three Gaussian functions are used to evaluate each pixel value in the target region. After using Mean-Shift algorithm to track the target region in the current frame, we update the Mixture Gaussian Model with the new...
Complex motion makes consecutive frames experience dramatic change, and thus becomes a barrier to object-tracking. Three factors contribute to more complexity of motion: longer sampling period,an moving object with complex appearance and nonrestraint movement, occlusion, which causes mean shift algorithm losing its target due to too low a Bhattacharyya coefficient. To treat it, mean shift algorithm...
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