Automatic textile image annotation by predicting emotional concepts from visual features

Image and Vision Computing

Volumn 28, Issue 3, 2010, Pages 526-537

  Shin, Yunhee ^a   Kim, Youngrae ^a   Kim, Eun Yi ^a  

^a Konkuk University   (South Korea)

Author keywords

Affective features; Automatic image annotation; Emotion recognition; Textile image retrieval: neural network

Indexed keywords

COLOR; FACE RECOGNITION; IMAGE ANALYSIS; IMAGE RETRIEVAL; NEURAL NETWORKS; TEXTILE PROCESSING; TEXTILES; WAVELET TRANSFORMS;

AUTOMATIC IMAGE ANNOTATION; BAYESIAN; COLOR QUANTIZATION; EMOTION RECOGNITION; EMOTIONAL CONCEPTS; K-MEANS CLUSTERING; MULTI-LAYERED; MULTI-LEVEL; PERCEPTRON; PREDICTION METHODS; PREDICTION SYSTEMS; TEXTILE IMAGES; VISUAL FEATURE;

TEXTILE INDUSTRY;

EID: 70449720538     PISSN: 02628856     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.imavis.2009.08.009     Document Type: Article

References (36)

1. Faloutsos C., Barber R., Flickner M., Hafner J., Niblack W., Petkovic D., and Equitz W. Efficient and effective querying by image content. Journal of Intelligent and Information System 3 3-4 (1994) 231-262
2. Pentland A., Picard R.W., and Scaroff S. Photobook: content-based manipulation for image databases. International Journal of Computer Vision 18 3 (1996) 233-254
3. J.R. Smith, S.F. Chang, VisualSeek: a fully automatic content based query system, in: Proc. of the 4th ACM Int. Conf. on Multimedia, 1996, pp. 87-98.
4. Kherfi M.L., Ziou D., and Bernardi A. Image retrieval from the world wide web: issues, techniques, and systems. ACM Computing Surveys 36 1 (2004) 35-67
5. Datta R., Joshi D., Li J., and Wang J.Z. Image retrieval: ideas influences and trends of the new age. ACM Computing Surveys 40 2 (2008) 5
6. J. Eakins, M. Graham, Content-based image retrieval, Technical Report, University of Northumbria at Newcastle, 1999.
7. Smeulders A.W., Worring M., Santini S., Gupta A., and Jain R. Content-based image retrieval at the end of the early years. IEEE Transactions on Pattern Analysis and Machine Intelligence 22 12 (2000) 1349-1380
8. Liu Y., Zhang D., Lu G., and Ma W. A survey of content-based image retrieval with high-level semantics. Pattern Recognition (2007) 262-282
9. Wang S., Jing F., He J., Du Q., and Zhang L. IGroup: Presenting Web Image Search Results in Semantic Clusters (2007), ACM Conference of Human Factors in Computing Systems (CHI) pp. 587-596
10. F. Jing, M. Li, L. Zhang, H.-J. Zhang, B. Zhang, Learning in region based image retrieval, in: Proc. of the Int. Conf. Image and Video Retrieval, 2003, pp. 206-215.
11. Li J., and Wang J.Z. Real-time computerized annotation of pictures. The IEEE Transactions on Pattern Analysis and Machine Intelligence 30 6 (2008) 985-1002
12. Kobayashi S. Color Image Scale (1991), Publishing of Kodansha
13. S. Kobayashi, K. Iwamatsu, Development of six methods of color psychological study, in: Proc. of the 8th Congress of the International Colour Association, 1997, pp. 727-730.
14. R. Datta, D Joshi, J. Li, J.Z. Wang, Studying aesthetics in photographic images using a computational approach, in: Proc. of the LNCS European Conf. on Computer Vision, vol. 3953, No. 3, 2006, pp. 288-301.
15. N.Y. Kim, Y. Shin, E.Y. Kim, Emotion-based textile indexing system using pattern recognition, in: Proc. of the IEEE Int. Symposium on Consumer Electronics, 2007, pp. 1-6.
16. S. Park, A study on affective space model for surface design, Thesis for the Degree of Doctor of Psychology in Yonsei Graduate School, 1999.
17. Kawamoto N., and Soen T. Objective evaluation of color design II. Color Research & Application 18 (1993) 260-266
18. Kim E.Y., Kim S., Koo H., Jeong K., and Kim J. Emotion-based textile indexing using colors and texture. International LNCS Conference on Fuzzy Systems and Knowledge Discovery 3613 (2005) 1077-1080
19. S. Kim, An emotion recognition framework for textile images, Thesis for the Degree of Doctor of Psychology in Konkuk Graduate School, 2007.
20. Um J., Eum K., and Lee J. A study of the emotional model of color pattern based on the adaptive fuzzy system on the neural network. Color Research & Application 27 (2002) 208-216
21. NCD (Nippon Color & Design Research Institute Inc.). Available from: .
22. IRI (Image Research Institute Inc.). Available from: .
23. World of Colour Emotion. Available from: .
24. da Pos O., and Green-Armytage P. Facial expressions, colours and basic emotions. Colour: Design & Creativity 1 1 (2008) 2 1-20
25. Likert R. A technique for the measurement of attitudes. Archives of Psychology 140 (1932) 1-55
26. Dawes J. Do data characteristics change according to the number of scale points used? An experiment using 5-point, 7-point and 10-point scales. International Journal of Market Research 50 1 (2008) 61-77
27. W.Y. Ma, B. Manjunath, Netra: a toolbox for navigating large image databases, in: Proc. of the IEEE Int. Conf. on Image Processing, 1997, pp. 568-571.
28. Li H., Doermann D., and Kia O. Automatic text detection and tracking in digital video. IEEE Transactions on Image Processing 9 1 (2000)
29. Y. Jing, S. Baluja, H. Rowley, Canonical image selection from the web, in: Proc. of 6th Int. Conf. on Image and Video Retrieval, 2007.
30. B.L. Saux, N. Boujemaa, Unsupervised robust clustering for image database categorization, in: Proc. of the Int. IEEE Conf. on Pattern Recognition, 2002.
31. J.S. Ju, Y. Shin, E.Y. Kim, Intelligent wheelchair (IW) interface using face and mouth recognition, in: Proc. of the ACM Int. Conf. on Intelligent User Interface, 2009, pp. 307-314.
32. G.H. John, P. Langley, Estimating continuous distributions in bayesian classifiers, in: Proc. of the ACM Int. Conf. on Artificial Intelligence, 1995, pp. 338-345.
33. H.-U. Bauer, T. Geisel, Dynamics of signal processing in feedback multilayer perceptrons, in: Proc. of the Int. Joint Conf. on Neural Networks, 1990, pp. 131-136.
34. Shin Y., Ju J.S., and Kim E.Y. Welfare interface implementation using multiple facial features tracking for the disabled people. Pattern Recognition Letters 29 13 (2008) 1784-1796
35. M. Turk, A. Pentland, Face recognition using eigenfaces, in: Proc. of the IEEE Conf. on Computer Vision and Pattern Recognition, 1991, pp. 586-591.
36. Belhumeur P., Hespanha J., and Kriegman D. Eigenfaces vs Fisherfaces: recognition using class specific linear projection. IEEE Transactions on Pattern Analysis and Machine Intelligence 19 7 (1997) 711