Multiple People Tracking Using an Appearance Model Based on Temporal Color

We present a method for detecting and tracking multiple people totally occluded or out of sight in a scene for some period of time in image sequences. Our approach is to use time weighted color information (i.e. the temporal color) for robust medium-term people tracking. The temporal color is the set of pairs of a color value and its associated weights. The weight is related to the size, duration and frequency of appearance of the color region, as well as the number of people adjacent to the target person. It assures our system to continuously track people moving in a group with occlusion. Most systems have built an appearance model for each person to solve occlusion problems. The appearance model contains certain information on the target person — color, shape, texture, position, velocity and face pattern. We use temporal color in the appearance model for the identification of the people occluded or out of sight in the scene upon their reappearance. Experimental results show that the temporal color is more stable than shape or intensity in various cases.

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Graph search: active appearance model based automated segmentation of retinal layers for optic nerve head centered OCT images

10.1117/12.2250168 ◽

2017 ◽

Author(s):

Enting Gao ◽

Fei Shi ◽

Weifang Zhu ◽

Chao Jin ◽

Min Sun ◽

...

Keyword(s):

Optic Nerve ◽

Optic Nerve Head ◽

Graph Search ◽

Appearance Model ◽

Active Appearance Model ◽

Automated Segmentation ◽

Retinal Layers ◽

Model Based ◽

Active Appearance

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An Adaptive Appearance Model Approach for Model-based Articulated Object Tracking

2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (CVPR'06) ◽

10.1109/cvpr.2006.52 ◽

2006 ◽

Cited By ~ 26

Author(s):

A.O. Balan ◽

M.J. Black

Keyword(s):

Object Tracking ◽

Appearance Model ◽

Model Based ◽

Articulated Object Tracking ◽

Model Approach

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Testing Colour Appearance Model Based UCS Using HDR, WCG and COMBVD Datasets

Color and Imaging Conference ◽

10.2352/issn.2169-2629.2021.29.381 ◽

2021 ◽

Vol 2021 (29) ◽

pp. 381-386

Author(s):

Xu Qiang ◽

Muhammad Safdar ◽

Ming Ronnier Luo

Keyword(s):

Correlation Coefficient ◽

Power Factor ◽

Marked Improvement ◽

Appearance Model ◽

Colour Difference ◽

Similar Performance ◽

Model Based ◽

Test Models ◽

Appearance Models ◽

Colour Appearance

Two colour appearance models based UCSs, CAM16-UCS and ZCAM-QMh, were tested using HDR, WCG and COMBVD datasets. As a comparison, two widely used UCSs, CIELAB and ICTCP, were tested. Metrics of the STRESS and correlation coefficient between predicted colour differences and visual differences, together with local and global uniformity based on their chromatic discrimination ellipses, were applied to test models' performance. The two UCSs give similar performance. The luminance parametric factor kL, and power factor γ, were introduced to optimize colour-difference models. Factors kL and γ of 0.75 and 0.5, gave marked improvement to predict the HDR dataset. Factor kL of 0.3 gave significant improvement in the test of WCG dataset. In the test of COMBVD dataset, optimization provide very limited improvement.

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