• Title/Summary/Keyword: 얼굴정규화

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3D Face Alignment and Normalization Based on Feature Detection Using Active Shape Models : Quantitative Analysis on Aligning Process (ASMs을 이용한 특징점 추출에 기반한 3D 얼굴데이터의 정렬 및 정규화 : 정렬 과정에 대한 정량적 분석)

  • Shin, Dong-Won;Park, Sang-Jun;Ko, Jae-Pil
    • Korean Journal of Computational Design and Engineering
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    • v.13 no.6
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    • pp.403-411
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    • 2008
  • The alignment of facial images is crucial for 2D face recognition. This is the same to facial meshes for 3D face recognition. Most of the 3D face recognition methods refer to 3D alignment but do not describe their approaches in details. In this paper, we focus on describing an automatic 3D alignment in viewpoint of quantitative analysis. This paper presents a framework of 3D face alignment and normalization based on feature points obtained by Active Shape Models (ASMs). The positions of eyes and mouth can give possibility of aligning the 3D face exactly in three-dimension space. The rotational transform on each axis is defined with respect to the reference position. In aligning process, the rotational transform converts an input 3D faces with large pose variations to the reference frontal view. The part of face is flopped from the aligned face using the sphere region centered at the nose tip of 3D face. The cropped face is shifted and brought into the frame with specified size for normalizing. Subsequently, the interpolation is carried to the face for sampling at equal interval and filling holes. The color interpolation is also carried at the same interval. The outputs are normalized 2D and 3D face which can be used for face recognition. Finally, we carry two sets of experiments to measure aligning errors and evaluate the performance of suggested process.

Effective Acne Detection using Component Image a* of CIE L*a*b* Color Space (CIE L*a*b* 칼라 공간의 성분 영상 a*을 이용한 효과적인 여드름 검출)

  • Park, Ki-Hong;Noh, Hui-Seong
    • Journal of Digital Contents Society
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    • v.19 no.7
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    • pp.1397-1403
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    • 2018
  • Today, modern people perceive skin care as part of their physical health care, and acne is a common skin disease problem that is found on the face. In this paper, an effective acne detection algorithm using CIE $L^*a^*b^*$ color space has been proposed. It is red when the pixel value of the component image $a^*$ is a positive number, so it is suitable for detecting acne in skin image. First, the skin image based on the RGB color space is subjected to light compensation through color balancing, and converted into a CIE $L^*a^*b^*$ color space. The extracted component image $a^*$ was normalized, and then the skin and acne area were estimated with the threshold values. Experimental results show that the proposed method detects acne more effectively than the conventional method based on brightness information, and the proposed method is robust against the reflected light source.

Functional Brain Mapping Using $H_2^{15}O$ Positron Emission Tomography ( II ): Mapping of Human Working Memory ($H_2^{15}O$ 양전자단층촬영술을 이용한 뇌기능 지도 작성(II): 작업 기억의 지도 작성)

  • Lee, Jae-Sung;Lee, Dong-Soo;Lee, Sang-Kun;Nam, Hyun-Woo;Kim, Seok-Ki;Park, Kwang-Suk;Jeong, Jae-Min;Chung, June-Key;Lee, Myung-Chul
    • The Korean Journal of Nuclear Medicine
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    • v.32 no.3
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    • pp.238-249
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    • 1998
  • Purpose: To localize and compare the neural basis of verbal and visual human working memory, we performed functional activation study using $H_2^{15}O$ PET. Materials and Methods: Repeated $H_2^{15}O$ PET scans with one control and three different activation tasks were performed on six right-handed normal volunteers. Each activation task was composed of 13 match-ing trials. On each trial, four targets, a fixation dot and a probe were presented sequentially and subject's task was to press a response button to indicate whether or not the probe was one of the previous targets. Short meaningful Korean words, simple drawings and monochromic pictures of human faces were used as matching objects for verbal or visual memory. All the images were spatially normalized and the differences between control and activation states were statistically analyzed using SPM96. Results: Statistical analysis of verbal memory activation with short words showed activation in the left Broca's area, promoter cortex, cerebellum and right cingulate gyrus. In verbal memory with simple drawings, activation was shown in the larger regions including where activated with short words and left superior temporal cortex, basal ganglia, thalamus, prefrontal cortex, anterior portion of right superior temporal gyrus and right infero-lateral frontal cortex. On the other hand, the visual memory task activated predominantly right-sided structures, especially inferior frontal cortex, supplementary motor cortex and superior parietal cortex. Conclusion: The results are consistent with the hypothesis of the laterality and dissociation of the verbal and visual working memory from the invasive electrophysiological studies and emphasize the pivotal role of frontal cortex and cingulate gyrus in working memory system.

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Pupil Data Measurement and Social Emotion Inference Technology by using Smart Glasses (스마트 글래스를 활용한 동공 데이터 수집과 사회 감성 추정 기술)

  • Lee, Dong Won;Mun, Sungchul;Park, Sangin;Kim, Hwan-jin;Whang, Mincheol
    • Journal of Broadcast Engineering
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    • v.25 no.6
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    • pp.973-979
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    • 2020
  • This study aims to objectively and quantitatively determine the social emotion of empathy by collecting pupillary response. 52 subjects (26 men and 26 women) voluntarily participated in the experiment. After the measurement of the reference of 30 seconds, the experiment was divided into the task of imitation and spontaneously self-expression. The two subjects were interacted through facial expressions, and the pupil images were recorded. The pupil data was processed through binarization and circular edge detection algorithm, and outlier detection and removal technique was used to reject eye-blinking. The pupil size according to the empathy was confirmed for statistical significance with test of normality and independent sample t-test. Statistical analysis results, the pupil size was significantly different between empathy (M ± SD = 0.050 ± 1.817)) and non-empathy (M ± SD = 1.659 ± 1.514) condition (t(92) = -4.629, p = 0.000). The rule of empathy according to the pupil size was defined through discriminant analysis, and the rule was verified (Estimation accuracy: 75%) new 12 subjects (6 men and 6 women, mean age ± SD = 22.84 ± 1.57 years). The method proposed in this study is non-contact camera technology and is expected to be utilized in various virtual reality with smart glasses.