• Title/Summary/Keyword: emotion-based image retrieval

Search Result 20, Processing Time 0.029 seconds

An Emotion-based Image Retrieval System by Using Fuzzy Integral with Relevance Feedback

  • Lee, Joon-Whoan;Zhang, Lei;Park, Eun-Jong
    • Proceedings of the IEEK Conference
    • /
    • 2008.06a
    • /
    • pp.683-688
    • /
    • 2008
  • The emotional information processing is to simulate and recognize human sensibility, sensuality or emotion, to realize natural and harmonious human-machine interface. This paper proposes an emotion-based image retrieval method. In this method, user can choose a linguistic query among some emotional adjectives. Then the system shows some corresponding representative images that are pre-evaluated by experts. Again the user can select a representative one among the representative images to initiate traditional content-based image retrieval (CBIR). By this proposed method any CBIR can be easily expanded as emotion-based image retrieval. In CBIR of our system, we use several color and texture visual descriptors recommended by MPEG-7. We also propose a fuzzy similarity measure based on Choquet integral in the CBIR system. For the communication between system and user, a relevance feedback mechanism is used to represent human subjectivity in image retrieval. This can improve the performance of image retrieval, and also satisfy the user's individual preference.

  • PDF

Query-by-emotion sketch for local emotion-based image retrieval (지역 감성기반 영상 검색을 위한 감성 스케치 질의)

  • Lee, Kyoung-Mi
    • Journal of Internet Computing and Services
    • /
    • v.10 no.6
    • /
    • pp.113-121
    • /
    • 2009
  • In order to retrieve images with different emotions in regions of the images, this paper proposes the image retrieval system using emotion sketch. The proposed retrieval system divides an image into $17{\times}17$ sub-regions and extracts emotion features in each sub-region. In order to extract the emotion features, this paper uses emotion colors on 160 emotion words from H. Nagumo's color scheme imaging chart. We calculate a histogram of each sub-region and consider one emotion word having the maximal value as a representative emotion word of the sub-region. The system demonstrates the effectiveness of the proposed emotion sketch and our experimental results show that the system successfully retrieves on the Corel image database.

  • PDF

Emotional Model via Human Psychological Test and Its Application to Image Retrieval (인간심리를 이용한 감성 모델과 영상검색에의 적용)

  • Yoo, Hun-Woo;Jang, Dong-Sik
    • Journal of Korean Institute of Industrial Engineers
    • /
    • v.31 no.1
    • /
    • pp.68-78
    • /
    • 2005
  • A new emotion-based image retrieval method is proposed in this paper. The research was motivated by Soen's evaluation of human emotion on color patterns. Thirteen pairs of adjective words expressing emotion pairs such as like-dislike, beautiful-ugly, natural-unnatural, dynamic-static, warm-cold, gay-sober, cheerful-dismal, unstablestable, light-dark, strong-weak, gaudy-plain, hard-soft, heavy-light are modeled by 19-dimensional color array and $4{\times}3$ gray matrix in off-line. Once the query is presented in text format, emotion model-based query formulation produces the associated color array and gray matrix. Then, images related to the query are retrieved from the database based on the multiplication of color array and gray matrix, each of which is extracted from query and database image. Experiments over 450 images showed an average retrieval rate of 0.61 for the use of color array alone and an average retrieval rate of 0.47 for the use of gray matrix alone.

Emotion from Color images and Its Application to Content-based Image Retrievals (칼라영상의 감성평가와 이를 이용한 내용기반 영상검색)

  • Park, Joong-Soo;Eum, Kyoung-Bae;Shin, Kyung-Hae;Lee, Joon-Whoan;Park, Dong-Sun
    • The KIPS Transactions:PartB
    • /
    • v.10B no.2
    • /
    • pp.179-188
    • /
    • 2003
  • In content-based image retrieval, the query is an image itself and the retrieval process is the process that seeking the similar images to the given query image. In this way of retrieval, the user has to know the basic physical features of target images that he wants to retrieve. But it has some restriction because to retrieve the target image he has to know the basic physical feature space such as color, texture, shape and spatial relationship. In this paper, we propose an emotion-based retrieval system. It uses the emotion that color images have. It is different from past emotion-based image retrieval in point of view that it uses relevance feedback to estimate the users intend and it is easily combined with past content-based image retrieval system. To test the performance of our proposed system, we use MPEG-7 color descriptor and emotion language such as "warm", "clean", "bright" and "delight" We test about 1500 wallpaper images and get successful result.lpaper images and get successful result.

Emotion Image Retrieval through Query Emotion Descriptor and Relevance Feedback (질의 감성 표시자와 유사도 피드백을 이용한 감성 영상 검색)

  • Yoo Hun-Woo
    • Journal of KIISE:Software and Applications
    • /
    • v.32 no.3
    • /
    • pp.141-152
    • /
    • 2005
  • A new emotion-based image retrieval method is proposed in this paper. Query emotion descriptors called query color code and query gray code are designed based on the human evaluation on 13 emotions('like', 'beautiful', 'natural', 'dynamic', 'warm', 'gay', 'cheerful', 'unstable', 'light' 'strong', 'gaudy' 'hard', 'heavy') when 30 random patterns with different color, intensity, and dot sizes are presented. For emotion image retrieval, once a query emotion is selected, associated query color code and query gray code are selected. Next, DB color code and DB gray code that capture color and, intensify and dot size are extracted in each database image and a matching process between two color codes and between two gray codes are peformed to retrieve relevant emotion images. Also, a new relevance feedback method is proposed. The method incorporates human intention in the retrieval process by dynamically updating weights of the query and DB color codes and weights of an intra query color code. For the experiments over 450 images, the number of positive images was higher than that of negative images at the initial query and increased according to the relevance feedback.

Interactive Genetic Algorithm for Content-based Image Retrieval

  • Lee, Joo-Young;Cho, Sung-Bae
    • Proceedings of the Korean Institute of Intelligent Systems Conference
    • /
    • 1998.06a
    • /
    • pp.479-484
    • /
    • 1998
  • As technology in a computer hardware and software advances, efficient information retrieval from multimedia database gets highly demanded. Recently, it has been actively exploited to retrieve information based on the stored contents. However, most of the methods emphasize on the points which are far from human intuition or emotion. In order to overcome this shortcoming , this paper attempts to apply interactive genetic algorithm to content-based image retrieval. A preliminary result with subjective test shows the usefulness of this approach.

  • PDF

Interactive emotion-based color image retrieval (대화형 감성기반 칼라영상 검색)

  • Eum Kyoung-Bae;Park Joong-Soo
    • Journal of the Korea Computer Industry Society
    • /
    • v.7 no.1
    • /
    • pp.17-22
    • /
    • 2006
  • Variable contents are extracted and used to improve the correctness of the retrieval in the content-based in age retrieval. This way use the physical feature for the retrieval. In this way of retrieval, the user has to know the basic physical features and spatial relationship of target images that he wants to retrieve. There are some restriction to reflect the user's intend. We need the retrieval system that reflect the user's intend. In this paper, we propose an emotion-based retrieval system. It is different from past emotion based image retrieval in point of view that it uses relevance feedback to estimate the users intend and it is easily combined with past content-based image retrieval system. The features and similarity measures are adopted from MPEG-7 color descriptors which are proper retrieval of large multimedia databases. We use wallpaper images for the experiment. The result shows that the system get successful result.

  • PDF

A Design and Implementation of Music & Image Retrieval Recommendation System based on Emotion (감성기반 음악.이미지 검색 추천 시스템 설계 및 구현)

  • Kim, Tae-Yeun;Song, Byoung-Ho;Bae, Sang-Hyun
    • Journal of the Institute of Electronics Engineers of Korea CI
    • /
    • v.47 no.1
    • /
    • pp.73-79
    • /
    • 2010
  • Emotion intelligence computing is able to processing of human emotion through it's studying and adaptation. Also, Be able more efficient to interaction of human and computer. As sight and hearing, music & image is constitute of short time and continue for long. Cause to success marketing, understand-translate of humanity emotion. In this paper, Be design of check system that matched music and image by user emotion keyword(irritability, gloom, calmness, joy). Suggested system is definition by 4 stage situations. Then, Using music & image and emotion ontology to retrieval normalized music & image. Also, A sampling of image peculiarity information and similarity measurement is able to get wanted result. At the same time, Matched on one space through pared correspondence analysis and factor analysis for classify image emotion recognition information. Experimentation findings, Suggest system was show 82.4% matching rate about 4 stage emotion condition.

Textile image retrieval integrating contents, emotion and metadata (내용, 감성, 메타데이터의 결합을 이용한 텍스타일 영상 검색)

  • Lee, Kyoung-Mi;Park, U-Chang;Lee, Eun-Ok;Kwon, Hye-Young;Cha, Eun-MI
    • Journal of Internet Computing and Services
    • /
    • v.9 no.5
    • /
    • pp.99-108
    • /
    • 2008
  • This paper proposes an image retrieval system which integrates metadata, contents, and emotions in textile images. First, the proposed system searches images using metadata. Among searched images, the system retrieves similar images based on color histogram, color sketch, and emotion histogram. To extract emotion features, this paper uses emotion colors which was proposed on 160 emotion words by H. Nagumo. To enhance the user's convenience, the proposed textile image retrieval system provides additional functions as like enlarging an image, viewing color histogram, viewing color sketch, and viewing repeated patterns.

  • PDF

An Image Retrieval Method based on Quantitative Emotion Evaluation on Color Harmony (색채조화의 정량적 감성평가에 기초한 이미지 검색법)

  • Kim, Don-Han;Jeong, Jae-Wook
    • Science of Emotion and Sensibility
    • /
    • v.15 no.1
    • /
    • pp.87-96
    • /
    • 2012
  • This paper proposes a Image retrieval system that searches the closest images to the user's emotional need and displays images with higher ratings of color harmony from Moon-Spencer's Color Harmony Theory first. Once an emotional adjective is placed, the system searches for images with colors that contain more elements derived from Aesthetic Measure results and displays in such order. In order to test reliability of the proposed emotion retrieval method based on Moon-Spencer's Color Harmony Theory, this study compared the order of Aesthetic Measure results with the user satisfaction ratings using 200 sample images. The analysis demonstrated that the participants' average satisfaction on 15 emotion adjectives selected for the study was 5.0 on a 7-point Likert scale. Correlation analyses were performed to test the consistency the orders between Aesthetic Measure values and user satisfaction ratings. Positive correlations above R=.5 were observed in all 14 emotion words except "Clear". These findings prove the potential of the proposed emotion retrieval system based on Moon-Spencer's Color Harmony Theory to effectively reflect user emotion in such visual stimulus search as image database.

  • PDF