• 제목/요약/키워드: Human behavior classification

검색결과 79건 처리시간 0.024초

Human Action Recognition Based on 3D Convolutional Neural Network from Hybrid Feature

  • Wu, Tingting;Lee, Eung-Joo
    • 한국멀티미디어학회논문지
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    • 제22권12호
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    • pp.1457-1465
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    • 2019
  • 3D convolution is to stack multiple consecutive frames to form a cube, and then apply the 3D convolution kernel in the cube. In this structure, each feature map of the convolutional layer is connected to multiple adjacent sequential frames in the previous layer, thus capturing the motion information. However, due to the changes of pedestrian posture, motion and position, the convolution at the same place is inappropriate, and when the 3D convolution kernel is convoluted in the time domain, only time domain features of three consecutive frames can be extracted, which is not a good enough to get action information. This paper proposes an action recognition method based on feature fusion of 3D convolutional neural network. Based on the VGG16 network model, sending a pre-acquired optical flow image for learning, then get the time domain features, and then the feature of the time domain is extracted from the features extracted by the 3D convolutional neural network. Finally, the behavior classification is done by the SVM classifier.

청소년이 지각한 부모의 물질주의 성향과 그에 따른 유형 분류 및 재정적 특성 분석 (Classification of Parents' Materialism Inclination Recognized by the Adolescents and Analysis of Their Financial Characteristics)

  • 홍은실
    • 가정과삶의질연구
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    • 제26권5호
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    • pp.377-390
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    • 2008
  • This paper investigated materialism inclination of the parents recognized by the adolescents and analysed the relationships between 5 categorized types about parents' materialism inclination and financial characteristics of the adolescents. Statistical analysis was achieved by using Cronbach'$\alpha$, paired t-test, one-way ANOVA, two-way ANOVA, Duncan's multiple range test, chi-square analysis, and Ward' hierarchical cluster analysis with a total of 801 questionnaires. The results are summarized as follows: First, the adolescents felt that calculated points of father and mother's materialism inclination were lower than median points and mother's inclination for materialism was higher than that of father. Second, five categories were classified according to materialism inclination of parents. First classified category was the type which showed both parents had little interest in materials and the second category was the type which father had strong interest in materials. The third one was the type which mother had strong interest in materials. The last two categories were the ones which both parents had much interest in materials. Final result of this study revealed that attitudes of the adolescents for materialism and money were higher for those whose parents had strong interest in materialism than those whose parents had little materialism interest. They showed not only the behaviors of impulsive and overspending consumption but also low financial satisfaction and high financial stress.

Lower Extremity Stiffness Characteristics in Running and Jumping: Methodology and Implications for Athletic Performance

  • Ryu, Joong Hyun
    • 한국운동역학회지
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    • 제28권1호
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    • pp.61-67
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    • 2018
  • Objective: The human body is often modelled as a spring-mass system. Lower extremity stiffness has been considered to be one of key factor in the performance enhancement of running, jumping, and hopping involved sports activities. There are several different classification of lower extremity stiffness consisting of vertical stiffness, leg stiffness, joint stiffness, as well as muscle and tendon stiffness. The primary purpose of this paper was to review the literature and describe different stiffness models and discuss applications of stiffness models while engaging in sports activities. In addition, this paper provided a current update of the lower extremity literature as it investigates the relationships between lower extremity stiffness and both functional performance and injury. Summary: Because various methods for measuring lower extremity stiffness are existing, measurements should always be accompanied by a detailed description including type of stiffness, testing method and calculation method. Moreover, investigator should be cautious when comparing lower extremity stiffness from different methods. Some evidence highlights that optimal degree of lower extremity stiffness is required for successful athletic performance. However, the actual magnitude of stiffness required to optimize performance is relatively unexplored. Direct relationship between lower extremity stiffness and lower extremity injuries has not clearly been established yet. Overall, high stiffness is potentially associate risk factors of lower extremity injuries although some of the evidence is controversial. Prospective injures studies are necessary to confirm this relationship. Moreover, further biomechanical and physiological investigation is needed to identify the optimal regulation of the lower limb stiffness behavior and its impact on athletic performance and lower limb injuries.

Wav2vec을 이용한 오디오 음성 기반의 파킨슨병 진단 (Diagnosis of Parkinson's disease based on audio voice using wav2vec)

  • 윤희진
    • 디지털융복합연구
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    • 제19권12호
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    • pp.353-358
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    • 2021
  • 노년기에 접어들면서 알츠하이머 다음으로 흔한 퇴행성 뇌 질환은 파킨슨병이다. 파킨슨병의 증상은 손 떨림, 행동의 느려짐, 인지기능의 저하 등 일상생활의 삶의 질을 저하시키는 요인이 된다. 파킨슨병은 조기진단을 통하여 병의 진행 속도를 늦출 수 있는 질환이다. 파킨슨병의 조기진단을 위해 오디오 음성 파일 입력으로 wav2vec을 이용하여 특징을 추출하고 딥러닝(ANN)으로 파킨슨병의 유무를 진단하는 알고리즘을 구현하였다. 오디오 음성 파일을 이용하여 파킨슨병을 진단하는 실험 결과 정확도는 97.47%로 나타났다. 기존의 뉴럴네트워크를 이용하여 파킨슨병을 진단하는 결과보다 좋은 결과를 나타냈다. 오디오 음성 파일을 wav2vec 이용으로 간단하게 실험을 과정을 줄일 수 있었으며, 실험 결과 향상된 결과를 얻을 수 있었다.

Comparing automated and non-automated machine learning for autism spectrum disorders classification using facial images

  • Elshoky, Basma Ramdan Gamal;Younis, Eman M.G.;Ali, Abdelmgeid Amin;Ibrahim, Osman Ali Sadek
    • ETRI Journal
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    • 제44권4호
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    • pp.613-623
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    • 2022
  • Autism spectrum disorder (ASD) is a developmental disorder associated with cognitive and neurobehavioral disorders. It affects the person's behavior and performance. Autism affects verbal and non-verbal communication in social interactions. Early screening and diagnosis of ASD are essential and helpful for early educational planning and treatment, the provision of family support, and for providing appropriate medical support for the child on time. Thus, developing automated methods for diagnosing ASD is becoming an essential need. Herein, we investigate using various machine learning methods to build predictive models for diagnosing ASD in children using facial images. To achieve this, we used an autistic children dataset containing 2936 facial images of children with autism and typical children. In application, we used classical machine learning methods, such as support vector machine and random forest. In addition to using deep-learning methods, we used a state-of-the-art method, that is, automated machine learning (AutoML). We compared the results obtained from the existing techniques. Consequently, we obtained that AutoML achieved the highest performance of approximately 96% accuracy via the Hyperpot and tree-based pipeline optimization tool optimization. Furthermore, AutoML methods enabled us to easily find the best parameter settings without any human efforts for feature engineering.

The Analysis of the Activity Patterns of Dog with Wearable Sensors Using Machine Learning

  • ;;김희철
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2021년도 춘계학술대회
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    • pp.141-143
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    • 2021
  • The Activity patterns of animal species are difficult to access and the behavior of freely moving individuals can not be assessed by direct observation. As it has become large challenge to understand the activity pattern of animals such as dogs, and cats etc. One approach for monitoring these behaviors is the continuous collection of data by human observers. Therefore, in this study we assess the activity patterns of dog using the wearable sensors data such as accelerometer and gyroscope. A wearable, sensor -based system is suitable for such ends, and it will be able to monitor the dogs in real-time. The basic purpose of this study was to develop a system that can detect the activities based on the accelerometer and gyroscope signals. Therefore, we purpose a method which is based on the data collected from 10 dogs, including different nine breeds of different sizes and ages, and both genders. We applied six different state-of-the-art classifiers such as Random forests (RF), Support vector machine (SVM), Gradient boosting machine (GBM), XGBoost, k-nearest neighbors (KNN), and Decision tree classifier, respectively. The Random Forest showed a good classification result. We achieved an accuracy 86.73% while the detecting the activity.

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퀘스트 시스템에 대한 게임플레이어의 감정패턴 분석 : 마비노기 Tutorial Mode를 중심으로 (Analysis of Emotion Pattern for Game Player on Quest System : Towards of Tutorial Mode in Mabinogi Game)

  • 김미진;송승근
    • 한국게임학회 논문지
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    • 제10권4호
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    • pp.15-22
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    • 2010
  • 본 논문은 RPG게임의 퀘스트 수행에 대한 플레이어의 감정패턴 분석을 그 목적으로 하고 있다. 인간의 다양한 인지행동 범주에 대한 선행연구를 바탕으로 게임플레이어의 행동범주를 5가지로 설정하고 범주에 해당하는 게임플레이 행동(Action)과 내용(Content)을 재정립하였다. 이를 바탕으로 스토리중심의 전개로 다양한 퀘스트 구성을 보여주는 마비노기(Mabinogi)게임의 초기단계(Tutorial Mode)를 퀘스트구조 및 인지행동별로 분류하여 초보 피험자 10명을 대상으로 감정데이터를 도출하고 게임플레이의 인지행동패턴과 도출감정사이의 상관관계를 모형화하였다. 이러한 연구결과는 게임 플레이어의 자극적 수준을 감정패턴으로 확인하여 특정단계의 퀘스트 설계 및 레벨 디자인의 구체화를 모색해 볼 수 있다. 또한 게임플레이 과정에서 플레이어의 감정변화는 재미요소의 표출형태이며 전체적으로 게임의 상위목표수행에 대한 호기심과 도전의식을 유발 시킬 수 있는 장치로 활용가능 하리라 본다.

마이크로 블로깅 서비스를 지원하기 위한 컨텍스트 모델 기반 자동 블로깅 시스템 (An Auto-blogging System based Context Model for Micro-blogging Service)

  • 박재민;이상용
    • 디지털융복합연구
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    • 제10권4호
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    • pp.341-346
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    • 2012
  • 소셜 네트워크 서비스의 가장 대표적인 마이크로 블로깅 서비스를 효과적으로 제공하기 위해 사용자가 자신의 현재 상황정보를 간편하게 기록하고 그 정보를 바탕으로 다른 사람들과 네트워크를 형성하고 유지하도록 하는 것이 중요하다. 하지만 모바일 환경에서 사용자가 자신의 정보를 매번 모바일 디바이스를 통해 직접 입력하는 것은 매우 번거로운 작업이다. 본 논문에서는 획득된 사용자 컨텍스트를 이용하여 사용자의 현재 행동과 다음 목적지를 추론한 후, 자동으로 문장을 생성하여 블로깅을 해주는 컨텍스트 모델 기반 자동 블로깅 시스템을 제안한다. 컨텍스트 모델을 생성하기 위해 사용자의 행동 추론은 나이브 베이즈 분류기를 이용하고, 이동중인 사용자의 다음 목적지 추론은 시퀀스 매칭을 이용하였다. 생성된 컨텍스트 모델을 기반으로 5W1H 구조를 이용하여 상황에 적합한 문장을 생성하여 자동으로 블로깅하였다. 제안한 방법의 정확도를 평가한 결과 평균 88.73%의 정확도를 보여 자동 블로깅 서비스가 가능함을 보여주었다.

대학생 소비자의 윤리적 소비행동에 따른 유형분류 및 특성분석 (A Study on Ethical Consumption Behaviors of College Students: Classification and Analysis according to the Ethical Consumption Behaviors)

  • 홍은실;신효연
    • 한국생활과학회지
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    • 제20권4호
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    • pp.801-817
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    • 2011
  • The purpose of this research was to explore the levels of ethical consumption of the college students and classify their types on ethical consumption behaviors. This research was conducted with university students living in Gwangju. Statistical analysis was achieved by using t-test, one-way ANOVA, Duncan's multiple range test, $X^2$, and Ward' hierarchical cluster analysis with a total of 761 questionnaires. The research results are summarized as follows: First, the overall ethical consumption average mark of college students was 3.14. Second, all surveyed college students were classified into five types based on the means scores of three dimension ethical consumption behaviors. A total 16.7% of students belonged to Type 1 (named as entire region active group) where students scored high points on three dimension ethical consumption behaviors. Type 2 (named as entire region average group) had about 41.6% of students whose scores were the average mark level in three dimension ethical consumption behaviors. Type 3 (named as future-oriented group) occupied 13.9% and this group scored low on the ethical consumption in commercial transaction but high on the ethical consumption for the future generation. Type 4 (named as commercial transaction oriented group) occupied 9.1% and this group scored low on the ethical consumption for contemporary humankind and the ethical consumption for the future generation but high on the ethical consumption in commercial transaction. Type 5 (named as entire region passive group) had 18.7% of students whose scores of three dimension ethical consumption behaviors were low.

연령별 대뇌 피질 두께의 성별 차이에 대한 형태학적 분석 (Morphological Analysis of Age-related Gender Differences in Cortical Thickness)

  • 서해석;김수현;윤의철
    • 대한의용생체공학회:의공학회지
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    • 제44권1호
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    • pp.53-63
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    • 2023
  • There have been many studies from the genetic system to physical activity and emotional expression such that there are gender differences. The purpose of this study was to determine how the structural characteristics of cortical thickness differ between males and females. This study used data from the Human Connectome Project (HCP). To analyze age-specific sexual dimorphisms of cortical thickness, selected 8-80 year old subjects were divided into five detailed age range groups according to each criterion. A total of 1,700 individual brain MRI T1 data were registered in stereotaxic space for analysis and classified into white matter (WM), gray matter (GM), and cerebro-spinal fluid (CSF). For surface-based analysis, the WM/GM surface was reconstructed from a spherical polygon model with 40962 vertices per hemisphere, and each vertex was extended to the GM/CSF boundary. Cortical thickness was then measured between each vertex using the t-link method. In the statistical analysis, intracranial volume was used as a covariate to exclude the effect of the difference in brain size of each individual, and the result of using age as a covariate was added to confirm the age effect within each group. Gender differences in cortical thickness had significant results by group. This may be an index to explain diseases with sexual dimorphism in prevalence or become a basis for explaining the characteristics of each sex that appear in behavior, personality, and aging. Therefore, the results of our study could be a criterion for age classification in future studies and for understanding 'normal' sexual dimorphism.