• Title/Summary/Keyword: contents recognition

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A Study on Hand Recognition in Image for Multimedia System (멀티미디어 시스템을 위한 영상내의 손 인식에 관한 연구)

  • Jung Hye-Won;Yang Hwan-Seok
    • The Journal of the Korea Contents Association
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    • v.5 no.2
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    • pp.267-274
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    • 2005
  • In this paper, we proposed an algorithm which cognize hand pose in real time using only image. Hand recognizes using edge orientation histogram which comes under a constant quantity of 2D appearance because hand pose is intricate. This method suit hand pose recognition in real time because it extracts hand space accurately, has little computation quantify, and is less sensitive to lighting change using color information in complicated background. Method which reduces recognition error using principal component analysis method to can recognize through hand shape presentation direction change is explained. A case that hand shape changes by turning 3D also by using this method is possible to recognize. Besides, principal component space creation time is reduced remarkably because edge directional data is used.

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Comparison of Adult and Child's Speech Recognition of Korean (한국어에서의 성인과 유아의 음성 인식 비교)

  • Yoo, Jae-Kwon;Lee, Kyoung-Mi
    • The Journal of the Korea Contents Association
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    • v.11 no.5
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    • pp.138-147
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    • 2011
  • While most Korean speech databases are developed for adults' speech, not for children's speech, there are various children's speech databases based on other languages. Because there are wide differences between children's and adults' speech in acoustic and linguistic characteristics, the children's speech database needs to be developed. In this paper, to find the differences between them in Korean, we built speech recognizers using HMM and tested them according to gender, age, and the presence of VTLN(Vocal Tract Length Normalization). This paper shows the speech recognizer made by children's speech has a much higher recognition rate than that made by adults' speech and using VTLN helps to improve the recognition rate in Korean.

Face Recognition by Combining Linear Discriminant Analysis and Radial Basis Function Network Classifiers (선형판별법과 레이디얼 기저함수 신경망 결합에 의한 얼굴인식)

  • Oh Byung-Joo
    • The Journal of the Korea Contents Association
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    • v.5 no.6
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    • pp.41-48
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    • 2005
  • This paper presents a face recognition method based on the combination of well-known statistical representations of Principal Component Analysis(PCA), and Linear Discriminant Analysis(LDA) with Radial Basis Function Networks. The original face image is first processed by PCA to reduce the dimension, and thereby avoid the singularity of the within-class scatter matrix in LDA calculation. The result of PCA process is applied to LDA classifier. In the second approach, the LDA process Produce a discriminational features of the face image, which is taken as the input of the Radial Basis Function Network(RBFN). The proposed approaches has been tested on the ORL face database. The experimental results have been demonstrated, and the recognition rate of more than 93.5% has been achieved.

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Face Recognition Method using Geometric Feature and PCA/LDA in Wavelet Domain (웨이브릿 영역에서 기하학적 특징과 PCA/LDA를 사용한 얼굴 인식 방법)

  • 송영준;김영길
    • The Journal of the Korea Contents Association
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    • v.4 no.3
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    • pp.107-113
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    • 2004
  • This paper improved the performance of the face recognition system using the PCA/LDA hybrid method based on the facial geometric feature and the Wavelet transform. Because the previous PCA/LDA methods have measured the similarity according to the formal dispersion, they could not reflect facial boundaries exactly In order to recover this defect, this paper proposed the method using the distance between eyes and mouth. If the difference of the measured distances on the query and the training images is over the given threshold, then the method reorders the candidate images according to energy feature vectors of eyes, a nose, and a chin. To evaluate the performance of the proposed method the computer simulations have been performed with four hundred facial images in the ORL database. The results showed that our method improves about 4% recognition rate over the previous PCA/LDA method.

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Driver's Behavioral Pattern in Driver Assistance System (운전자 사용자경험기반의 인지향상 시스템 연구)

  • Jo, Doori;Shin, Donghee
    • Journal of Digital Contents Society
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    • v.15 no.5
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    • pp.579-586
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    • 2014
  • This paper analyzes the recognition of driver's behavior in lane change using context-free grammar. In contrast to conventional pattern recognition techniques, context-free grammars are capable of describing features effectively that are not easily represented by finite symbols. Instead of coordinate data processing that should handle features in multiple concurrent events respectively, effective syntactic analysis was applied for patterning of symbolic sequence. The findings proposed the effective and intuitive method for drivers and researchers in driving safety field. Probabilistic parsing for the improving this research will be the future work to achieve a robust recognition.

Performance Improvement of Fake Discrimination using Time Information in CNN-based Signature Recognition (CNN 기반 서명인식에서 시간정보를 이용한 위조판별 성능 향상)

  • Choi, Seouing-Ho;Jung, Sung Hoon
    • Journal of Digital Contents Society
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    • v.19 no.1
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    • pp.205-212
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    • 2018
  • In this paper, we propose a method for more accurate fake discrimination using time information in CNN-based signature recognition. To easily use the time information and not to be influenced by the speed of signature writing, we acquire the signature as a movie and divide the total time of the signature into equal numbers of equally spaced intervals to obtain each image and synthesize them to create signature data. In order to compare the method using the proposed signature image and the method using only the last signature image, various signature recognition methods based on CNN have been experimented in this paper. As a result of experiment with 25 signature data, we found that the method using time information improves performance in fake discrimination compared to the existing method at all experiments.

Effect of Subtitle and Infographic of YouTube Content on the memory of Audience (유튜브 콘텐츠의 자막과 인포그래픽이 수용자의 기억에 미치는 영향)

  • Park, DugChun
    • Journal of Korea Multimedia Society
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    • v.25 no.10
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    • pp.1468-1474
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    • 2022
  • This is an empirical study to find out whether subtitles and infographics can affect the recognition and recall memory of YouTube users. In this study, a total of 104 university students were divided into 4 groups and exposed to 4 types of contents according to the presence or absence of subtitles and infographics. After the subjects watched YouTube content, they responded to the level of their memory through a survey. As a result of the analysis, the subtitles used in YouTube contents did not affect the recall memory of the audience, and the infographic did not affect the recognition memory of the audience. However, when subtitles were used for YouTube content, the audience's recognition memory was found to be high at a statistically significant level, and when infographics were used for YouTube content, the audience's recall memory was found to be high at a statistically significant level. The significance of this study can be found in that the effects of subtitles and infographics that appeared in the audience effect of legacy media such as newspapers and broadcasting were also found in YouTube, a new video content media.

Multimodal Attention-Based Fusion Model for Context-Aware Emotion Recognition

  • Vo, Minh-Cong;Lee, Guee-Sang
    • International Journal of Contents
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    • v.18 no.3
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    • pp.11-20
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    • 2022
  • Human Emotion Recognition is an exciting topic that has been attracting many researchers for a lengthy time. In recent years, there has been an increasing interest in exploiting contextual information on emotion recognition. Some previous explorations in psychology show that emotional perception is impacted by facial expressions, as well as contextual information from the scene, such as human activities, interactions, and body poses. Those explorations initialize a trend in computer vision in exploring the critical role of contexts, by considering them as modalities to infer predicted emotion along with facial expressions. However, the contextual information has not been fully exploited. The scene emotion created by the surrounding environment, can shape how people perceive emotion. Besides, additive fusion in multimodal training fashion is not practical, because the contributions of each modality are not equal to the final prediction. The purpose of this paper was to contribute to this growing area of research, by exploring the effectiveness of the emotional scene gist in the input image, to infer the emotional state of the primary target. The emotional scene gist includes emotion, emotional feelings, and actions or events that directly trigger emotional reactions in the input image. We also present an attention-based fusion network, to combine multimodal features based on their impacts on the target emotional state. We demonstrate the effectiveness of the method, through a significant improvement on the EMOTIC dataset.

A study on exhibition contents application plan based on image recognition augmented reality (이미지 인식 증강현실 기반 전시콘텐츠 활용 방안)

  • Lee, il-soo;Kim, sang-heon
    • Proceedings of the Korea Contents Association Conference
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    • 2015.05a
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    • pp.143-144
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    • 2015
  • 최근 문화기술분야의 기술적 진보로 인하여 다양한 기술을 활용한 전시회가 이루어지고 있는데 전시회에서 기술을 활용하는 범주는 편협한 경우가 대부분이기 때문에 크게 세 가지의 사례를 통해 문제점을 파악하고, 증강현실(AR) 기술을 활용한 체험전시 방안에 대해 검토해 보고자 한다.

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Influencing Factors for Repurchase Intention in e-Learning Sites

  • Lee, Myung-Moo;Chung, In-Keun
    • Proceedings of the CALSEC Conference
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    • 2005.03a
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    • pp.96-100
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    • 2005
  • This study examines the effects of the characteristics of educational contents, brand recognition, educational management and technical support on the repurchase intention mediated by overall satisfaction, trust and commitment in e-Learning sites. A survey of experienced users was conducted to collect data. The reliability and validity of data were tested by explanatory factor analysis, Cornbach's alpha coefficient, confirmatory factor analysis and correlation analysis. Also, the structural equation mode (SEM) analysis was performed to test the usefulness of the model. The results of the study are as follows: Educational contents, educational management and technical support were found to have positive effects on overall satisfaction. And educational contents and brand recognition were found to have positive effects on trust and commitment. And trust and overall satisfaction were found to have mediating effects on repurchase intention.

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