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Local Directional Ternary Pattern for Facial Expression Recognition
Byungyong Ryu,Ramirez Rivera, Adin,Jaemyun Kim,Oksam Chae IEEE 2017 IEEE TRANSACTIONS ON IMAGE PROCESSING - Vol.26 No.12
<P>This paper presents a new face descriptor, local directional ternary pattern (LDTP), for facial expression recognition. LDTP efficiently encodes information of emotion-related features (i.e., eyes, eyebrows, upper nose, and mouth) by using the directional information and ternary pattern in order to take advantage of the robustness of edge patterns in the edge region while overcoming weaknesses of edge-based methods in smooth regions. Our proposal, unlike existing histogram-based face description methods that divide the face into several regions and sample the codes uniformly, uses a two-level grid to construct the face descriptor while sampling expression-related information at different scales. We use a coarse grid for stable codes (highly related to non-expression), and a finer one for active codes (highly related to expression). This multi-level approach enables us to do a finer grain description of facial motions while still characterizing the coarse features of the expression. Moreover, we learn the active LDTP codes from the emotion-related facial regions. We tested our method by using person-dependent and independent cross-validation schemes to evaluate the performance. We show that our approaches improve the overall accuracy of facial expression recognition on six data sets.</P>
한민수(Min-su Han),류병용(Byungyong Ryu),김재면(Jaemyun Kim),송기훈(Gihun Song),채옥삼(Oksam Chae) 대한전자공학회 2015 대한전자공학회 학술대회 Vol.2015 No.6
We propose a novel local micro pattern, Symmetric Directional Pattern (SDP), in order to perform facial expression recognition. SDP extracts edge directions and responses information from the local neighbors using symmetric Sobel masks, and encodes the prominent direction effectively. According to magnitude of edge responses, SDP deals with edge texture and smooth areas differently. With these properties, SDP becomes robust against random noise and illumination changes, and provides better discrimination power about other existing expression databases also present the outstanding recognition accuracy of the proposed method.
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>
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.