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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>
Gender Recognition from Facial Sketch Images using Local Adaptive Structural Pattern
Md Tauhid Bin Iqbal(엠디 타우휘드 이크발),Oksam Chae(채옥삼) Korean Institute of Information Scientists and Eng 2018 정보과학회논문지 Vol.45 No.8
In this paper, we present a new edge-based local image descriptor named Local Adaptive Structural Pattern (LASP), for the recognition of gender from facial sketch images. LASP generates eight directional edge responses of a pixel by applying Kirsch compass masks and selects top two directions to represent the local texture structure. Moreover, LASP applies an adaptivelyselected threshold on the top directional response in order to filter the low response of the flat pixels producing spurious codes. The top two Kirsch directions represent the local texture structure appropriately, whereas the imposed threshold on the top Kirsch-response differentiates the spurious codes generated from the flat regions, yielding a compact description of the facial sketches. We evaluate the performance of LASP in existing facial sketch datasets for the recognition of gender and observe improved accuracies compared to existing local descriptors.
Person-Independent Facial Expression Recognition with Histograms of Prominent Edge Directions
( Farkhod Makhmudkhujaev ),( Md Tauhid Bin Iqbal ),( Md Rifat Arefin ),( Byungyong Ryu ),( Oksam Chae ) 한국인터넷정보학회 2018 KSII Transactions on Internet and Information Syst Vol.12 No.12
This paper presents a new descriptor, named Histograms of Prominent Edge Directions (HPED), for the recognition of facial expressions in a person-independent environment. In this paper, we raise the issue of sampling error in generating the code-histogram from spatial regions of the face image, as observed in the existing descriptors. HPED describes facial appearance changes based on the statistical distribution of the top two prominent edge directions (i.e., primary and secondary direction) captured over small spatial regions of the face. Compared to existing descriptors, HPED uses a smaller number of code-bins to describe the spatial regions, which helps avoid sampling error despite having fewer samples while preserving the valuable spatial information. In contrast to the existing Histogram of Oriented Gradients (HOG) that uses the histogram of the primary edge direction (i.e., gradient orientation) only, we additionally consider the histogram of the secondary edge direction, which provides more meaningful shape information related to the local texture. Experiments on popular facial expression datasets demonstrate the superior performance of the proposed HPED against existing descriptors in a person-independent environment.