스포츠 휴먼브랜드 속성이 브랜드 동일시, 소비자-브랜드 관계 및 확장된 브랜드 구매의도에 미치는 영향

이정학(Lee, Jeong-Hak),이경률(Li, Jing-Lu),김재환(Kim Jae-Hwan),이성빈(Lee, Sung-Bin) 한국사회체육학회 2015 한국사회체육학회지 Vol.0 No.59

This study aimed to determine how human brand attributes relate to human brand identification, consumer-human brand relationship, and expanded human brand purchase intention. Using the snowball sampling of the non-probability sampling, online questionnaire method was conducted for 15 days in August, 2014 and the target were citizens in Seoul and Gyeonggi-do. Except for 15 data which were not seriously taken, 435 responses were used as valid samples. PASW 21.0 was used to conduct frequency analysis, exploratory factor analysis, reliability analysis, and correlation analysis, and AMOS 21.0 was used to conduct confirmatory factor analysis and structure equation modeling. The conclusions drawn from this study are as follows. First, the reliability and attractiveness of human brand attributes were found to have a positive effect on human brand identification, but professionalism had no effect on human brand identification. Second, human brand identification had a positive influence on the consumer-human brand relationship. Third, human brand identification had a positive impact on expanded human brand purchase intention. Lastly, the consumer-human brand relationship had a positive influence on expanded human brand purchase intention.

Body-movement-based human identification using convolutional neural network

Batchuluun, Ganbayar,Naqvi, Rizwan Ali,Kim, Wan,Park, Kang Ryoung Elsevier 2018 expert systems with applications Vol.101 No.-

<P><B>Abstract</B></P> <P>Biometric technology based on human gait identifies humans at a far distance even if the individual's face is covered, hidden, or not visible to cameras in dark environments. Previous studies based on human gait were conducted considering both bright and dark environments for human identification in surveillance systems. The studies conducted in low-illumination environments (dark environments) are based on side view images (horizontal walking) of subjects. However, there are cases in which people only show the front and back views of their bodies while they are walking in low-illumination corridors. In these views, it is difficult to identify humans by using conventional features such as cycle, cadence, stride length of walking, and distance between points (ankle, knee, and hip). Additionally, the cases of problems such as people carrying cellphones and/or small personal items (a purse, bag, clothes, etc.) have critical effects on the accuracy of human identification. To overcome these problems, we propose a new human identification technique, which is based on the front and back view images of a human, captured by using a thermal camera sensor. Our technique uses movements of the human body for identification, particularly movement of the head, shoulders, and legs. We have used a convolutional neural network for feature extraction and classification in this study. Five datasets were compiled by collecting data of 80 people including men and women in both bright and dark environments. The experimental results with our collected data and open database showed a higher performance by using our method compared to those of previous studies.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Our method is body movement-based human identification using front and back view. </LI> <LI> Our identification method is robust to the cases of people carrying items or with various poses. </LI> <LI> Deep learning method using thermal difference image-based three-channel inputs is used. </LI> <LI> Our collected database and trained CNN are public to other researchers. </LI> </UL> </P>

EMG 신호 기반 Artificial Neural Network을 이용한 사용자 인식

김상호(Sang-Ho Kim),류재환(Jae-Hwan Ryu),이병현(Byeong-Hyeon Lee),김덕환(Deok-Hwan Kim) 대한전자공학회 2016 전자공학회논문지 Vol.53 No.4

최근 다양한 생체신호를 이용한 사용자 인식 방법들이 연구되고 있으며 그 중에 보행을 기반으로 한 사용자 인식 방법이 활발하게 연구되고 있다. 본 논문에서는 사람이 보행할 때 사용되는 허벅지 근육의 EMG(Electromyography) 신호를 기반으로 사용자를 인식하는 방법을 제안하였다. 근전도 신호의 RMS, MAV, VAR, WAMP, ZC, SSC, IEMG, MMAV1, MMAV2, MAVSLP, SSI, WL를 특징으로 산출하여 ANN(Artificial Neural Network) 분류기를 통해 사용자를 인식한다. 사용자 인식에 적합한 근육과 특징을 선별하기 위해서 근육 및 특징별 인식률을 비교한 결과 대퇴직근, 반건양근, 외측광근이 사용자 인식에 적합한 근육으로 나타났으며, MAV, ZC, IEMG, MMAV1, MAVSLP 특징이 사용자 인식에 적합한 특징으로 나타났다. 실험결과 모든 특징들과 채널들을 사용했을 때의 인식률은 평균 99.7%을 보였고 사용자 인식에 적합하다고 판단되는 3개의 근육, 5개의 특징을 사용했을 때의 인식률은 평균 96%을 보였다. 따라서 사용자의 보행에 따른 EMG 신호 기반 사용자 인식이 가능함을 확인하였다. 그리고 사용자 인식에 적합한 소수의 채널과 특징을 사용하여 사용자 인식하는데 적용될 수 있음을 확인하였다. Recently, human identification using various biological signals has been studied and human identification based on the gait has been actively studied. In this paper, we propose a human identification based on the EMG(Electromyography) signal of the thigh muscles that are used when walking. Various features such as RMS, MAV, VAR, WAMP, ZC, SSC, IEMG, MMAV1, MMAV2, MAVSLP, SSI, WL are extracted from EMG signal data and ANN(Artificial Neural Network) classifier is used for human identification. When we evaluated the recognition ratio per channel and features to select approptiate channels and features for human identification. The experimental results show that the rectus femoris, semitendinous, vastus lateralis are appropriate muscles for human identification and MAV, ZC, IEMG, MMAV1, MAVSLP are adaptable features for human identification. Experimental results also show that the average recognition ratio of method of using all channels and features is 99.7% and that of using selected 3 channels and 5 features is 96%. Therefore, we confirm that the EMG signal can be applied to gait based human identification and EMG signal based human identification using small number of adaptive muscles and features shows good performance.

Parameter Identification of an Unknown Object in Human-Robot Collaborative Manipulation

Jayoung Jang,Jong Hyeon Park 제어로봇시스템학회 2020 제어로봇시스템학회 국제학술대회 논문집 Vol.2020 No.10

In human-robot collaborative manipulation of an object, if the robot knows the intention of the human, the efficiency of the work would greatly increase. For the robot to know of the human intention, it should have the information of the force applied by the human, which can be more accurately if it can estimate the inertial and dimensional parameters online. However, the force applied by the human will disturb the parameter identification process. This paper presents a strategy to identify the inertial and dimensional parameters of an unknown object online for physical human-robot interactions. Extended Kalman filter is used for identification under the assumption that the force applied by the human is an unknown external disturbance. This approach was evaluated in simulations of physical human-robot object manipulation task.

Antecedents to Strong Identification with Fan Communities of Human Brands

한정수 한국산업경영학회 2017 한국산업경영학회 발표논문집 Vol.2017 No.1

As the human brands are becoming more popular and influential, their influences on the lives of people also getting more significant. Fans of certain human brands create or participate in the fan community to seek like-minded others for sharing same interests and enthusiasms and . In doing so, fan community members identify themselves with the fan community and support the human brand they like by doing community-based group behaviors. Thus, well-established fan communities are very influential and provide great marketing opportunities, suggesting the importance of the studying the fan communities. This study examined the dynamics among human brand, fans, and fan community identification. Results of the study found that attachment to human brand influences fan community identification positively. Furthermore, one community-related variable, human brand-fan community similarity, and one consumer-related variable, need for belongingness, were found to strengthen the relationship between human brand attachment and fan community identification. Implications that the results of this study provides are also discussed.

휴먼 브랜드 팬 커뮤니티 동일시의 선행요인에 관한 연구

한정수(Han JeongSoo),신선진(Shin SeonJin) 한국산업경영학회 2017 경영연구 Vol.32 No.2

휴먼 브랜드의 인기가 높아질수록 이들이 사람들에게 미치는 영향 또한 커지고 중요해지고 있다. 특정 휴먼 브랜드의 팬들은 자신들이 좋아하는 휴먼 브랜드에 대한 관심과 열정을 공유하고자 팬 커뮤니티를 만들거나 가입해서 활동을 하는 행동을 보이기도 한다. 이러한 과정에서 이들은 자신이 속한 팬 커뮤니티와 자신을 동일시하기도 하고 이런 동일시를 바탕으로 커뮤니티 기반의 그룹 활동을 통해서 자신들이 좋아하는 휴먼 브랜드를 지지하는 행동을 보이기도 한다. 이에 본 연구는 팬 커뮤니티 동일시에 영향을 미치는 선행요인을 찾고 이 관계를 더 강하게 하는 조절변수를 살펴보았다. 연구결과, 휴먼 브랜드에 대한 애착이 팬 커뮤니티 동일시에 긍정적으로 영향을 주는 선행변수로, 더 나아가, 이러한 관계를 더 강하게 만드는 요인으로 휴먼 브랜드-팬 커뮤니티 유사 성과 소속감 욕구가 조절변수의 역할을 하는 것으로 나타났다. 본 연구의 결과는 관련 분야에 이론적인 시사점 뿐 아니라 실무적 시사점 또한 제공한다. As the human brands are becoming more popular and influential, their influences on the lives of people also getting more significant. Fans of certain human brands create or participate in the fan community to seek like-minded others for sharing same interests and enthusiasms. In doing so, fan community members identify themselves with the fan community and support the human brand they like by doing communitybased group behaviors. Thus, well-established fan communities are very influential and provide great marketing opportunities, suggesting the importance of the studying the fan communities. This study examined the dynamics among human brand, fans, and fan community identification. Results of the study found that attachment to human brand influences fan community identification positively. Furthermore, one community-related variable, human brand-fan community similarity, and one consumer-related variable, need for belongingness, were found to strengthen the relationship between human brand attachment and fan community identification. Implications that the results of this study provides are also discussed.

Microbial Forensics: Human Identification

Yong-Bin Eom 대한의생명과학회 2018 Biomedical Science Letters Vol.24 No.4

Microbes is becoming increasingly forensic possibility as a consequence of advances in massive parallel sequencing (MPS) and bioinformatics. Human DNA typing is the best identifier, but it is not always possible to extract a full DNA profile namely its degradation and low copy number, and it may have limitations for identical twins. To overcome these unsatisfactory limitations, forensic potential for bacteria found in evidence could be used to differentiate individuals. Prokaryotic cells have a cell wall that better protects the bacterial nucleoid compared to the cell membrane of eukaryotic cells. Humans have an extremely diverse microbiome that may prove useful in determining human identity and may even be possible to link the microbes to the person responsible for them. Microbial composition within the human microbiome varies across individuals. Therefore, MPS of human microbiome could be used to identify biological samples from the different individuals, specifically for twins and other cases where standard DNA typing doses not provide satisfactory results due to degradation of human DNA. Microbial forensics is a new discipline combining forensic science and microbiology, which can not to replace current STR analysis methods used for human identification but to be complementary. Among the fields of microbial forensics, this paper will briefly describe information on the current status of microbiome research such as metagenomic code, salivary microbiome, pubic hair microbiome, microbes as indicators of body fluids, soils microbes as forensic indicator, and review microbial forensics as the feasibility of microbiome-based human identification.

감시카메라의 범인 식별 -초기 영국사례에 대한 영상학, 인지심리학적 연구-

박상우 ( Sang Woo Park ) 한국사진학회 2011 AURA Vol.0 No.24

This paper meta-analyze from image and cognitive psychological point of view the preceding researches on the effects of CCTV on criminal identification, which have been made by the British criminalists and cognitive psychologists since 1990s. By doing so, I aim to reveal the powers and the limits of CCTV for human identification. The conclusion is summarized as follows. First of all, there are many limits of CCTV for the human identification from a image point of view. First, CCTV images give an operator too massive and boring visual information at the same time. Second, it is difficult to compare and identify the CCTV images, because they are not standardized. Third, it is hard to extract a full face photo of a criminal from CCTV images. Fourth, it is difficult to identify exactly the human face of which characteristics vary continuously among individuals. In addition, from cognitive psychological point of view, the effect of CCTV for human identification depends on the observer`s prior knowledge of the observed. It is revealed that the observer cannot identify strangers easily from very high quality CCTV image. On the contrary, the observer can identify the observed known, even from the very poor quality CCTV image. This is where the significance of CCTV for human identification is most obvious.

Dynamic Time Warping based Identification using Gabor Feature of Adaptive Motion Model for Walking Humans

박준범,이영현,고한석 제어·로봇·시스템학회 2009 International Journal of Control, Automation, and Vol.7 No.5

In this paper, we propose a novel feature extraction method for the identification of humans. The main objective of our method is to identify each human being by extracting the Gabor feature based on the Adaptive Motion Model (AMM) for the motion of humans. In our method, the adaptive motion model, which can represent the temporal motion for each walking human is first made from the sequence images and, then, the Gabor features of the eight directions which can represent the spatial motion information for humans are extracted. The proposed feature extraction method can make a more accurate motion model by adjusting the weight between the previous and current model for each person. Moreover, our method has the advantage of allowing more information such as the Gabor features for the eight directions extracted from the AMM. Since the conventional method uses the face feature for each human being, it has disadvantages in the case of images of small size, while our method has better identification performance this case, because it only uses the spatio-temporal motion information. Finally, we identify each person by finding the minimum value of the extended dynamic time warping (DTW) for the eight Gabor features. The accuracy of the identification conducted using the proposed feature is better than that of the conventional method using the Gait Energy Image (GEI) and Face Image feature.

Eys Detection and Tracking and Eye Gaze Estimation

Bhargavi Nadella 사단법인 미래융합기술연구학회 2015 아시아태평양융합연구교류논문지 Vol.1 No.2

Dynamic Eye-look identification and following have been a dynamic examination held in the previous years as it changes it up of uses. It is viewed as a significant untraditional technique for human PC association. Head development identification has likewise gotten specialists' consideration and enthusiasm as it has been observed to be a basic and successful cooperation technique. Both innovations are viewed as the most straightforward elective interface techniques. They serve an extensive variety of seriously crippled individuals who are left with insignificant engine capacities. For both eye following and head development discovery, a few diverse methodologies have been proposed and used to execute diverse calculations for these advancements. In spite of the measure of examination done on both advancements, specialists are as yet attempting to and powerful routines to utilize viably in different applications. This paper shows a condition of-workmanship study for eye following and head development identification techniques proposed in the writing. Illustrations of distinctive ends of utilizations for both innovations, for example, human computer connection, driving help frameworks, and assistive innovations are likewise examined. Despite dynamic exploration and noteworthy advancement in the most recent 30 years, eye recognition and following stays testing because of the uniqueness of eyes, impediment, and variability in scale, area, and light conditions. Information on eye area and points of interest of eye developments have various applications and are vital in face discovery, biometric recognizable proof, and specific human-PC association errands. This paper audits current advance and best in class in video-based eye recognition and following keeping in mind the end goal to recognize promising strategies and also issues to be further tended to.