Adaptive window method with sizing vectors for reliable correlation-based target tracking

Success of a tracking method depends largely on choosing the suitable window size as soon as the target size changes in image sequences. To achieve this goal, we propose a fast tracking algorithm based on adaptively adjusting tracking window. Firstly, tracking window is divided into four edge subwindows, and a background subwindow around it. Then, by calculating the spatiotemporal gradient power ratios of the target in each subwindow, four proper expansion vectors are associated with any tracking window sides such that the occupancy rate of the target in tracking window should be maintained within a specified range. In addition, since temporal changing of target is evaluated in calculating these vectors, we estimate overall target displacement by sum of expansion vectors. Experimental results using various real video sequences show that the proposed algorithm successfully track an unknown textured target in real time, and is robust to dynamic occlusions in complex noisy backgrounds.

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“…7, we quantify the well-known center position error E p , and the window sizing error E s as follows 6,8 :…”

Section: Robust and Fast Tracking Algorithm In Video Sequences 315mentioning

confidence: 99%

Robust and Fast Tracking Algorithm in Video Sequences by Adaptive Window Sizing Using a Novel Analysis on Spatiotemporal Gradient Powers

Moallem

Memarmoghaddam²,

Ashourian

2007

J CIRCUIT SYST COMP

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“…If ratio is less then window is decreased one pixel, otherwise the window is increased. In (Chien, 2000), correlation window is adapted by modeling with motion vectors. Direction and magnitude of contraction or expansion depend on simple image processing.…”

Section: Visual Tracking Of Objectsmentioning

confidence: 99%

Subpixel Visual Tracking Based on Adaptive Strategies

Barrón¹,

Cruz²,

Altamirano

2006

Proceedings of the First International Conference on Computer Vision Theory and Applications

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Several applications based on visual tracking need a better accuracy to perform a more reliable analysis of the objects in scene. However, it is necessary to deal with environments with different atmospheric conditions. Object dynamics can affect tracking throughout time. In this work, a tracking method with subpixel measurements is described, where quality of the state estimate of the object is enhanced. The proposed scheme is robust in scenes with occlusions and changes in appearance of the target. The target model is adapted to size changes of the object, avoiding aperture problem and integration with false information. The state of the object and its aspect along time are estimated. Each pixel is modeled by a random variable because the set of pixels represents the non-observable surface of target where real value of pixels can be affected by noise. This assumption allows the design of a gradual scheme for model updating. Subpixel precision in tracking is based on an iterative method that uses the similitude surface between the target model and the current image of the object on tracking.

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“…Adaptive window methods have been applied at least in median filtering 1 and template matching [2][3][4][5][6][7][8][9] . In several research papers, adaptive window size template matching has been applied to disparity map creation in stereo vision algorithms [2][3][4][5][6][7] .…”

Section: Introductionmentioning

confidence: 99%

“…In several research papers, adaptive window size template matching has been applied to disparity map creation in stereo vision algorithms [2][3][4][5][6][7] . Another typical application is target tracking [8][9] . On the contrary, there does not seem to be any applications on strain measurements, although a lot of papers on digital image correlation based strain measurements have been published.…”

Section: Introductionmentioning

confidence: 99%

Dynamic template size control in digital image correlation based strain measurements

2007

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Image matching is a common procedure in computer vision. Usually the size of the image template is fixed. If the matching is done repeatedly, as e.g. in stereo vision, object tracking, and strain measurements, it is beneficial, in terms of computational cost, to use as small templates as possible. On the other hand larger templates usually give more reliable matches, unless e.g. projective distortions become too great. If the template size is controlled locally dynamically, both computational efficiency and reliability can be achieved simultaneously. Adaptive template size requires though that a larger template can be sampled anytime.This paper introduces a method to adaptively control the template size in a digital image correlation based strain measurement algorithm. The control inputs are measures of confidence of match. Some new measures are proposed in this paper, and the ones found in the literature are reviewed. The measures of confidence are tested and compared with each other as well as with a reference method using templates of fixed size. The comparison is done with respect to computational complexity and accuracy of the algorithm. Due to complex inter-actions of the free parameters of the algorithm, random search is used to find an optimal parameter combination to attain a more reliable comparison. The results show that with some confidence measures the dynamic scheme outperforms the static reference method. However, in order to benefit from the dynamic scheme, optimization of the parameters is needed.

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Adaptive window method with sizing vectors for reliable correlation-based target tracking

Cited by 12 publications

References 6 publications

Robust and Fast Tracking Algorithm in Video Sequences by Adaptive Window Sizing Using a Novel Analysis on Spatiotemporal Gradient Powers

Robust and Fast Tracking Algorithm in Video Sequences by Adaptive Window Sizing Using a Novel Analysis on Spatiotemporal Gradient Powers

Subpixel Visual Tracking Based on Adaptive Strategies

Dynamic template size control in digital image correlation based strain measurements

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