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Skin detection using statistics of small amount of training data
Shoyaib, M.,Abdullah-Al-Wadud, M.,Chae, O.,Byungyong, R. IET 2012 Electronics letters Vol.48 No.2
<P>A skin detection approach based on combination of the statistics of multiple sources is presented. As long as the scarcity of available training data (with ground truth) is very common considering practical applications, such a fusion offers a much better classification of skin pixels compared to the state-of-the-art methods. Experiments on a renowned dataset result in a similar decision.</P>
Multiple object tracking with partial occlusion handling using salient feature points
Naushad Ali, M.M.,Abdullah-Al-Wadud, M.,Lee, S.L. North-Holland [etc ; Elsevier Science Ltd 2014 Information sciences Vol.278 No.-
Handling occlusion has been a challenging task in object tracking. In this paper, we propose a multiple object tracking method in the presence of partial occlusion using salient feature points. We first extract the prominent feature points from each target object, and then use a particle filter-based approach to track the feature points in image sequences based on various attributes such as location, velocity and other descriptors. We then detect and revise the feature points that have been tracked incorrectly. The main idea is that, even if some feature points are not successfully tracked due to occlusion or poor imaging condition, the other correctly tracked features can collectively perform the corrections on their behalf. Finally, we track the objects using the correctly tracked feature points through a Hough-like approach, and the object bounding boxes are updated using the relative locations of these feature points. Experimental results demonstrate that our method is proficient in providing accurate human tracking as well as appropriate occlusion handling, compared to the existing methods.
Directional Age-Primitive Pattern (DAPP) for Human Age Group Recognition and Age Estimation
Bin Iqbal, Md Tauhid,Shoyaib, Mohammad,Byungyong Ryu,Abdullah-Al-Wadud, M.,Oksam Chae IEEE 2017 IEEE transactions on information forensics and sec Vol.12 No.11
<P>An appropriate aging description from face image is the prime influential factor in human age recognition, but still there is an absence of a specially engineered aging descriptor, which can characterize discernible facial aging cues (e.g., craniofacial growth, skin aging) from a detailed and more finer point of view. To address this issue, we propose a local face descriptor, directional age-primitive pattern (DAPP), which inherits discernible aging cue information and is functionally more robust and discriminative than existing local descriptors. We introduce three attributes for coding the DAPP description. First, we introduce Age-Primitives encoding aging related to the most crucial texture primitives, yielding a reasonable and clear aging definition. Second, we introduce an encoding concept dubbed as Latent Secondary Direction, which preserves compact structural information in the code avoiding uncertain codes. Third, a globally adaptive thresholding mechanism is initiated to facilitate more discrimination in a flat and textured region. We apply DAPP on separate age group recognition and age estimation tasks. Applying the same approach to both of these tasks is seldom explored in the literature. Carefully conducted experiments show that the proposed DAPP description outperforms the existing approaches by an acceptable margin.</P>