• Journal of Korea Multimedia Society
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• v.10 no.7
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• pp.827-837
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• 2007

Conventional color-based object tracking using Mean Shift algorithm does not provide appropriate result when initial color distribution disappears. In this paper we propose a tracking algorithm that updates the object color sample when the color is changing. Mean Shift analysis is first used to derive the object candidate with maximum increase in density direction from current position. The color information of object is updated iteratively. The proposed algorithm achieves accurate tracking of objects when initial color samples are changed and finally disappeared. The validity of the effective approach is illustrated by the experimental results.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.136-141
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• 2009

This paper proposed a framework for handover method in continuously tracking a person of interest across cooperative pan-tilt-zoom (PTZ) cameras. The algorithm here is based on a robust non-parametric technique for climbing density gradients to find the peak of probability distributions called the mean shift algorithm. Most tracking algorithms use only one cue (such as color). The color features are not always discriminative enough for target localization because illumination or viewpoints tend to change. Moreover the background may be of a color similar to that of the target. In our proposed system, the continuous person tracking across cooperative PTZ cameras by mean shift tracking that using color and shape histogram to be feature distributions. Color and shape distributions of interested person are used to register the target person across cameras. For the first camera, we select interested person for tracking using skin color, cloth color and boundary of body. To handover tracking process between two cameras, the second camera receives color and shape cues of a target person from the first camera and using linear color calibration to help with handover process. Our experimental results demonstrate color and shape feature in mean shift algorithm is capable for continuously and accurately track the target person across cameras.

• Korean Journal of Optics and Photonics
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• v.26 no.2
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• pp.110-114
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• 2015

We propose a reflective cholesteric liquid crystal cell with reduced color shift, using dichroic dyes. Color-shifted light is absorbed by dye molecules in the proposed dye-doped cholesteric liquid crystal (DDCLC) cell. We have shown that the color shift can be reduced by increasing the concentration of dye molecules in the proposed DDCLC cell.

• Journal of KIISE:Software and Applications
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• v.34 no.10
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• pp.937-944
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• 2007

In this paper, we propose multiple human tracking with an moving stereo camera. The tracking process is based on mean shift algorithm which is using color information of the target. Color based tracking approach is invariant to translation and rotation of the target but, it has several problems. Because of mean shift uses color distribution, it is sensitive to color distribution of background and targets. In order to solve this problem, we combine color and depth information of target. Also, we build human body part model to handle occlusions and we have created adaptive box scale. As a result, the proposed method is simple and efficient to track multiple humans in real time.

• Journal of Information Display
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• v.8 no.3
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• pp.17-21
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• 2007

We introduce a new electrode structure for the patterned vertical alignment (PVA) mode, which has a lower color-shift at large viewing angle than the one-domain VA mode. By manipulating the period of electrode structure, we can make more multi-domains and use the existing fabrication processes without having to use additional materials.

• ETRI Journal
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• v.34 no.3
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• pp.399-409
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• 2012

In this paper, we propose a new color histogram model for object tracking. The proposed model incorporates the color arrangement of the target that encodes the relative spatial distribution of the colors inside the object. Using the color arrangement, we can determine which color bin is more reliable for tracking. Based on the proposed color histogram model, we derive a mean shift framework using a modified Bhattacharyya distance. In addition, we present a method of updating an object scale and a target model to cope with changes in the target appearance. Unlike conventional mean shift based methods, our algorithm produces satisfactory results even when the object being tracked shares similar colors with the background.

• Proceedings of the Optical Society of Korea Conference
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• 2007.02a
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• pp.54-55
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• 2007

• 한국정보디스플레이학회:학술대회논문집
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• 2008.10a
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• pp.753-756
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• 2008

We analyzed the problem of the typical definition of the viewing angle, where the contrast ratio is higher than 1:10 and suggest the new definition of the viewing angle by considering the contrast ratio, color shift, luminance and gamma shift in the viewing direction all together.

• Journal of the Institute of Convergence Signal Processing
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• v.18 no.2
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• pp.68-75
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• 2017

This study deals with a color-based tracking method of a moving object effectively in case that the color of the moving object is same as or similar to that of background. The CamShift algorithm, which is the representative color-based tracking method, shows unstable tracking when the color of moving objects exists in the background. In order to overcome the drawback, this paper proposes the CamShift algorithm merged with depth information of the object. Depth information can be obtained from Kinect device which measures the distance information of all pixels in an image. Experimental result shows that the proposed tracking method, the Camshift merged with depth information of the tracking object, makes up for the unstable tracking of the existing CamShift algorithm and also shows improved tracking performance in comparison with only CamShift algorithm.

• The Journal of the Korea Contents Association
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• v.6 no.9
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• pp.19-27
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• 2006

Mean shift procedure is applied for the data points in the joint spatial-range domain and achieves a high quality. However, a color image is segmented differently according to the inputted spatial parameter or range parameter and the demerit is that the image is broken into many small regions in case of the small parameter. In this paper, to improve this demerit, we propose the method that groups similar regions using region merging method for over-segmented images. The proposed method converts a over-segmented image in RGB color space into in HSI color space and merges similar regions by hue information. Here, to preserve edge information, the region merge constraints are used to decide whether regions are merged or not. After then, we merge the regions in RGB color space for non-processed regions in HSI color space. Experimental results show the superiority in region's segmentation results.