연령에 따른 한국인 손 피부색 차이 분석

홍다검,이희경,이정현 한국인체미용예술학회 2016 한국인체미용예술학회지 Vol.17 No.1

Recently, nail industry trends have been shifting from polish nail to gel nail. Because of the popularity of gel nail, the criteria for customers to choose colors have significantly changed. Therefore, there has been a rising demand for a nail color which goes well with skin color, not with the color of clothes, makes the hand more beautiful. Unlike a face, hand skin color isn’t corrected through makeup. Therefore, it is more difficult to find a color which is well matched with the skin tone. In this sense, the accurate analysis and classification of hand skin color which is the first step in the selection of nail color are required. However, it’s still very hard to find studies on hand skin color. To figure out the characteristics of Koreans’ hand skin color by age, this study analyzed differences in hand skin color by age after measuring the tone of the back of the hand and conducting quantitative analysis against 300 women living in Busan, Ulsan and Gyeongnam. The results revealed statistically significant difference (p.001). As the respondents were younger, a bright skin tone was observed. According to analysis on the distribution by the rank, ‘20s’ was the highest with 46% among those with a bright skin tone within top 100 ranks. In top 300 ranks, in contrast, ‘50s’ was the highest with 46% while ‘20s (8%)’ was the lowest. In terms of a skin tone, there was a considerable difference between ‘20s’ and ‘50s.’ Even though no big difference was found between ‘30s’ and ‘40s,’ a skin tone was brighter in the latter.

연령에 따른 한국인 손 피부색 차이 분석

홍다검ㆍ이희경ㆍ이정현(Da Geom HongㆍHee kyung LeeㆍJeong Hyun Lee) 한국인체미용예술학회 2016 한국인체미용예술학회지 Vol.17 No.1

Recently, nail industry trends have been shifting from polish nail to gel nail. Because of the popularity of gel nail, the criteria for customers to choose colors have significantly changed. Therefore, there has been a rising demand for a nail color which goes well with skin color, not with the color of clothes, makes the hand more beautiful. Unlike a face, hand skin color isn’t corrected through makeup. Therefore, it is more difficult to find a color which is well matched with the skin tone. In this sense, the accurate analysis and classification of hand skin color which is the first step in the selection of nail color are required. However, it’s still very hard to find studies on hand skin color. To figure out the characteristics of Koreans’ hand skin color by age, this study analyzed differences in hand skin color by age after measuring the tone of the back of the hand and conducting quantitative analysis against 300 women living in Busan, Ulsan and Gyeongnam. The results revealed statistically significant difference (p.001). As the respondents were younger, a bright skin tone was observed. According to analysis on the distribution by the rank, ‘20s’ was the highest with 46% among those with a bright skin tone within top 100 ranks. In top 300 ranks, in contrast, ‘50s’ was the highest with 46% while ‘20s (8%)’ was the lowest. In terms of a skin tone, there was a considerable difference between ‘20s’ and ‘50s.’ Even though no big difference was found between ‘30s’ and ‘40s,’ a skin tone was brighter in the latter.

Dynamic Hand Gesture Trajectory Recognition Based on Block Feature and Skin-Color Clustering

Zhang Qiu-yu,Lv Lu,Lu Jun-chi,Zhang Mo-yi,Duan Hong-xiang 보안공학연구지원센터 2016 International Journal of Multimedia and Ubiquitous Vol.11 No.12

In recent years, dynamic hand gesture recognition has been a research hotspot of human-computer interaction. Since most existing algorithms contain problems with high computational complexity, poor real-time performance and low recognition rate, which cannot satisfy the need of many practical applications. Moreover, key frames obtained by inter-frame difference degree algorithm contain less information, which leads to less identified species and lower recognition rate. To solve these problems, we present a dynamic hand gesture trajectory recognition method based on the theory of block feature to extract key frames and the skin-color clustering’s hand gesture segmentation. Firstly, this method extracts block feature of degree of difference between frames in hand gesture sequence to select key frames accurately. Secondly, the method based on skin-color clustering is applied to obtain the area of hand gesture after segmenting hand gestures from images. Finally, hidden Markov model (HMM), in which the angle data of hand gesture trajectories are input, is used for modeling and identifying dynamic hand gestures. Experimental results show that the method of key-frame extraction is used to obtain information of dynamic hand gestures accurately, which would improve the recognition rate of dynamic hand gesture recognition and, at the same time, can guarantee the real-time of hand gesture recognition system. The average recognition rate is up to 86.67%, and the average time efficiency is 0.39s.

Dynamic Hand Gesture Segmentation Method Based on Improved Kalman Filter and Weighted Skin-Color Model

Zhang Qiu-yu,Lu Jun-chi,Wei Hui-yi,Zhang Mo-yi,Duan Hong-xiang 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.6

In order to improve the problems of segmentation accuracy and real-time existing in dynamic hand gesture under complex backgrounds, this paper presents a kind of dynamic hand gesture segmentation method based on improved Kalman filter and weighted skin-color model. Firstly, improved Kalman filter is utilized to process hand gesture image of hand gesture video sequences and get rough hand gesture results. Secondly, weighted skin-color model is applied to process rough results of hand gesture segmentation and segment hand gesture. Finally, morphological method is utilized to deal with gesture segmentation result, getting rid of the holes in the hand gesture’s binary image to realize the segmentation of dynamic hand gesture. Experiments show that the proposed method can segment hand gesture from dynamic hand gesture video sequences with complex backgrounds effectively. And the accuracy of hand gesture segmentation is high.

강인한 손가락 끝 추출과 확장된 CAMSHIFT 알고리즘을 이용한 자연스러운 Human-Robot Interaction 을 위한 손동작 인식

이래경(Lae-Kyoung Lee),안수용(Su-Yong An),오세영(Se-Young Oh) 제어로봇시스템학회 2012 제어·로봇·시스템학회 논문지 Vol.18 No.4

In this paper, we propose a robust fingertip extraction and extended Continuously Adaptive Mean Shift (CAMSHIFT) based robust hand gesture recognition for natural human-like HRI (Human-Robot Interaction), Firstly, for efficient and rapid hand detection, the hand candidate regions are segmented by the combination with robust YCbCr skin color model and haar-like features based adaboost. Using the extracted hand candidate regions, we estimate the palm region and fingertip position from distance transformation based voting and geometrical feature of hands. From the hand orientation and palm center position, we find the optimal fingertip position and its orientation. Then using extended CAMSHIFT, we reliably track the 2D hand gesture trajectory with extracted fingertip. Finally, we applied the conditional density propagation (CONDENSATION) to recognize the pre-defined temporal motion trajectories. Experimental results show that the proposed algorithm not only rapidly extracts the hand region with accurately extracted fingertip and its angle but also robustly tracks the hand under different illumination, size and rotation conditions. Using these results, we successfully recognize the multiple hand gestures.

인간과 로봇과의 상호 작용을 위한 강인한 손가락 끝 추출과 손 추척 알고리즘

이래경,안수용,오세영 제어로봇시스템학회 2011 제어로봇시스템학회 국내학술대회 논문집 Vol.2011 No.5

In this paper, we propose a robust fingertip extraction and hand tracking method for Human-Robot Interaction (HRI) with dynamic hand gestures. The hand candidate regions are segmented by applying YCbCr skin color model and morphological and blob-based analysis. Based on extracted hand regions, we estimate the palm region and fingertip position from distance transform and geometrical features of hands. Using hand orientation and palm center, we find the optimal fingertip position and its orientation with classified hand. Then using extended CAMSHIFT, we track the hand gesture with extracted fingertip. Experimental results show that the proposed algorithm not only can efficient extract the hand region with accurately extracted fingertip and its angle but also robustly track the hand under different illumination, size and rotation conditions.

수화 인식을 위한 얼굴과 손 추적 알고리즘

박호식,배철수,Park, Ho-Sik,Bae, Cheol-Soo 한국통신학회 2006 韓國通信學會論文誌 Vol.31 No.11C

본 논문에서는 수화 인식을 위한 얼굴 및 손 추적시스템을 제안한다. 제안된 시스템은 검출 및 추적 단계로 구분된다. 검출 단계에서는 신호의 주체인 얼굴과 손에 위치한 피부 특징을 이용하였다. CbCr 공간에서의 타원 모델을 구성하여 피부 색상을 검출하고 피부 영역을 분할한다. 그리고 크기와 얼굴 특징을 이용하여 얼굴과 손 영역을 정의한다. 추적 단계에서는 동작 추정을 위하여 첫 번째 손 영역으로 예측된 다음의 손위치를 연산함으로써 두 번째 손의 영역을 유도해낸다. 그러나 갑작스런 움직임의 속도 변화가 있을 경우 연속된 프레임에서 추적된 위치는 부정확하였다. 이러한 점을 해결하고자 손 영역에 대하여 반복적인 재연산을 수행하여 적응적으로 영역을 찾음으로써 오차를 보정하도록 하였다. 실험 결과 제안된 방법은 기존의 방법보다 4%의 처리 시간이 증가된 반면, 예측 오차는 96.87%까지 감소시킬 수 있었다. In this paper, we develop face and hand tracking for sign language recognition system. The system is divided into two stages; the initial and tracking stages. In initial stage, we use the skin feature to localize face and hands of signer. The ellipse model on CbCr space is constructed and used to detect skin color. After the skin regions have been segmented, face and hand blobs are defined by using size and facial feature with the assumption that the movement of face is less than that of hands in this signing scenario. In tracking stage, the motion estimation is applied only hand blobs, in which first and second derivative are used to compute the position of prediction of hands. We observed that there are errors in the value of tracking position between two consecutive frames in which velocity has changed abruptly. To improve the tracking performance, our proposed algorithm compensates the error of tracking position by using adaptive search area to re-compute the hand blobs. The experimental results indicate that our proposed method is able to decrease the prediction error up to 96.87% with negligible increase in computational complexity of up to 4%.

Hand Gesture Recognition using Improved Hidden Markov Models

Xu, Wenkai,Lee, Eung-Joo Korea Multimedia Society 2011 멀티미디어학회논문지 Vol.14 No.7

In this paper, an improved method of hand detecting and hand gesture recognition is proposed, it can be applied in different illumination condition and complex background. We use Adaptive Skin Threshold (AST) to detect the areas of hand. Then the result of hand detection is used to hand recognition through the improved HMM algorithm. At last, we design a simple program using the result of hand recognition for recognizing "stone, scissors, cloth" these three kinds of hand gesture. Experimental results had proved that the hand and gesture can be detected and recognized with high average recognition rate (92.41%) and better than some other methods such as syntactical analysis, neural based approach by using our approach.

디지털 기기 작동 제어를 위한 핸드모션 인식 기법의 개발 및 구현

허문행(Mun-Haeng Heo),송특섭(Teuk-Seob Song) 한국정보기술학회 2009 Proceedings of KIIT Conference Vol.2009 No.-

많은 분야에 활용되고 있는 영상인식은 점점 더 다양한 분야에 적용되어 증가되고 있는 추세이다. 특히 인식분야에서도 손동작인식은 다양한 기능으로 활용이 가능하기 때문에 많은 관심이 요구된다. 본 논문에서는 손동작인식을 위한 핑거영역을 추출하고 추출한 알고리즘을 바탕으로 카메라에 응용시켰다. 과정은 다음과 같다. 먼저 색상을 이용하여 손을 구분하였다. 손가락만을 남기기 위해 손바닥을 제거했다. 손의 중심을 구하고 중심으로부터 일정한 너비를 구하는 방법으로 손바닥 부분을 제거했다. 원하는 동작을 인식하기 위해 손가락과 그룹화 하여 그 그룹의 수를 저장해 손가락의 수를 구별했다. 그 기능을 응용하여 손가락으로 V자 동작을 취할 시 자동으로 촬영이 되는 프로그램을 구현하였다. Image-Recognition in many fields is steadily increasing a trend and spreading many diverse fields. Since Hand-Gesture Recognition can be apply various areas. It attracts the interest of many researchers. In this paper, we use a color and divide a hand. We remove the palm of the hand to remain a finger. We get the center of the hand and remove the palm of the hand to use a method which get a width of the hand from the center. We distinguish fingers grouped to a detection of the hand movement which save the number of the fingers. We make the program which automatically take a picture when the fingers are like 'V'.

Dynamic Manipulation of a Virtual Object in Marker-less AR system Based on Both Human Hands

( Junchul Chun ),( Byungsung Lee ) 한국인터넷정보학회 2010 KSII Transactions on Internet and Information Syst Vol.4 No.4

This paper presents a novel approach to control the augmented reality (AR) objects robustly in a marker-less AR system by fingertip tracking and hand pattern recognition. It is known that one of the promising ways to develop a marker-less AR system is using human`s body such as hand or face for replacing traditional fiducial markers. This paper introduces a real-time method to manipulate the overlaid virtual objects dynamically in a marker-less AR system using both hands with a single camera. The left bare hand is considered as a virtual marker in the marker-less AR system and the right hand is used as a hand mouse. To build the marker-less system, we utilize a skin-color model for hand shape detection and curvature-based fingertip detection from an input video image. Using the detected fingertips the camera pose are estimated to overlay virtual objects on the hand coordinate system. In order to manipulate the virtual objects rendered on the marker-less AR system dynamically, a vision-based hand control interface, which exploits the fingertip tracking for the movement of the objects and pattern matching for the hand command initiation, is developed. From the experiments, we can prove that the proposed and developed system can control the objects dynamically in a convenient fashion.