Background compensation using Hough transformation

Pham, Xuan Dai; Cho, Jung Uk; Jeon, Jae Wook

doi:10.1109/robot.2008.4543571

Cited by 3 publications

(2 citation statements)

References 10 publications

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“…Because the search range is limited using the HT, the GHT method can reduce the outliers that affect average error. In addition, because the proposed method is based on the HT, its Hough-related parameters were the same as those in the MHT based method [15]: the number of binary images N was 32, the tolerance value T was 0.1, the scale range was [0.9, 1.1] (  [48.04 o , 42.30 o ]), and the resolution was  =  = 0.0003. Moreover, for the MHT, the number of iterations was 2, and the reduction factor  = 2,  = 1; and for the proposed GHT, the vote threshold T v was 10.…”

Section: Resultsmentioning

confidence: 99%

“…The GHT based method described in the present paper represents part of a continuum of research on developing a novel background compensation method. Our previously published work, which is based on multi-resolution HT [14], has been described in [15] with the goal of achieving high accuracy. In the present study, we combined GA with HT, because GA is extremely effective for solving combinatorial optimization problems.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Scaling-Translation Parameter Estimation using Genetic Hough Transform for Background Compensation

Nguyen

Pham²,

Jeon³

2011

KSII TIIS

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Background compensation plays an important role in detecting and isolating object motion in visual tracking. Here, we propose a Genetic Hough Transform, which combines the Hough Transform and Genetic Algorithm, as a method for eliminating background motion. Our method can handle cases in which the background may contain only a few, if any, feature points. These points can be used to estimate the motion between two successive frames. In addition to dealing with featureless backgrounds, our method can successfully handle motion blur. Experimental comparisons of the results obtained using the proposed method with other methods show that the proposed approach yields a satisfactory estimate of background motion.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Scaling-Translation Parameter Estimation using Genetic Hough Transform for Background Compensation

Nguyen

Pham²,

Jeon³

2011

KSII TIIS

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Global motion compensation for image sequences and motion object detection

Zhang

Xie

2010

2010 International Conference on Computer Application and System Modeling (ICCASM 2010)

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Cooperative Moving Object Segmentation using Two Cameras based on Background Subtraction and Image Registration

Cui

Jiang

2014

JMM

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Moving camera, such as PTZ (pan-tilt-zoom) camera, has been widely applied in visual surveillance system. However, it's difficult to extract moving objects because of the dynamic background caused by the camera motion. In this paper, a novel framework for moving object segmentation exploiting two cameras collaboration is presented by combining background subtraction and image registration method. The proposed method uses one static camera to capture large-view images at low resolution, and one moving camera (i.e. PTZ camera) to capture local-view images at high resolution. Different with methods using a single moving camera, the moving objects can be effectively segmented in the static camera image by background subtraction method. Then image registration method can be applied to extract moving region in the moving camera image. To deal with the resolution and intensity discrepancy between two synchronized images, we design a practical three-step image registration method, which has higher registration accuracy than traditional feature based method. Experimental results on outdoor scene demonstrate the effectiveness and robustness of proposed approach.

show abstract

Background compensation using Hough transformation

Cited by 3 publications

References 10 publications

Scaling-Translation Parameter Estimation using Genetic Hough Transform for Background Compensation

Scaling-Translation Parameter Estimation using Genetic Hough Transform for Background Compensation

Global motion compensation for image sequences and motion object detection

Cooperative Moving Object Segmentation using Two Cameras based on Background Subtraction and Image Registration

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