• Journal of Broadcast Engineering
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• v.18 no.5
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• pp.680-690
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• 2013

In this paper, we propose a real-time temporal synchronization and compensation algorithm in stereoscopic video. Many temporal asynchronies are caused in the video editing stage and due to different transmission delays. These temporal asynchronies can degrade the perceived 3D quality. The goal of temporal alignment is to detect and to measure the temporal asynchrony and recover synchronization of the two video streams. In order to recover synchronization of the two video streams, we developed a method to detect asynchronies between the left and the right video streams based on a novel spatiogram information, which is a richer representation, capturing not only the values of the pixels but their spatial relationships as well. The proposed novel spatiogram additionally includes the changes of the spatial color distribution. Furthermore, we propose a block-based method for detection of the pair frame instead of one frame-based method. Various 3D experiments demonstrate the effectiveness of the proposed method.

• Journal of Broadcast Engineering
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• v.19 no.6
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• pp.896-906
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• 2014

In this paper, a real-time dual-mode temporal synchronization and compensation method based on a new reliability measure in stereoscopic video is proposed. The goal of temporal alignment is to detect the temporal asynchrony and recover synchronization of the two video streams. The accuracy of the temporal synchronization algorithm depends on the 3DTV contents. In order to compensate the temporal synchronization error, it is necessary to judge whether the result of the temporal synchronization is reliable or not. Based on our recently developed temporal synchronization method[1], we define a new reliability measure for the result of the temporal synchronization method. Furthermore, we developed a dual-mode temporal synchronization method, which uses a usual texture matching method and the temporal spatiogram method[1]. The new reliability measure is based on two distinctive features, a dynamic feature for scene change and a matching distinction feature. Various experimental results show the effectiveness of the proposed method. The proposed algorithms are evaluated and verified through an experimental system implemented for 3DTV.

• ETRI Journal
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• v.29 no.5
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• pp.697-699
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• 2007

Spatiograms are histograms augmented with spatial means and covariances to capture a richer description of the target. We present a particle filtering framework for region-based tracking using spatiograms. Unlike mean shift, the framework allows for non-differentiable similarity measures to compare two spatiograms; we present one such similarity measure, a combination of a recent weighting scheme and histogram intersection. Experimental results show improved performance with the new measure as well as the importance of global spatial information for tracking. The performance of spatiograms is compared with color histograms and several texture histogram methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.1
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• pp.1-10
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• 2012

In this paper, we propose a new class of color histogram model suitable for object tracking. In addition to the pixel count, each bin of the proposed model also contains the spatial mean and the average value of the pixels located at a certain distance from the mean location of the bin. Using the proposed color histogram model, we derive a mean shift procedure using the modified Bhattacharyya distance. Unlike most mean shift based methods, our algorithm performs well even when the object being tracked shares similar colors with the background. Experimental results demonstrate improved tracking performance over existing methods.