Abstract
This paper presents a face image annotation system based on latent semantic indexing and rules. To achieve annotation, visual and symbolic features are integrated. Two features are corresponding to lengths and/or widths of face parts and keywords, respectively. In order to develop annotation mechanism, it is required to vary the dimensions of the spaces which are constructed by the latent semantic indexing, and to represent direct relationships among features. Associated symbolic features to visual features are represented in rules based on decision trees. Co-occurrence relationships among keywords are represented in association rules.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
References
Chellappa, R., Wilson, C.L., Sirohey, S.: Human and Machine Recognition of Faces: A Survey. Proceedings of the IEEE 83(5) (1995)
Datta, R., Ge, W., Li, J., Wang, Z.: Toward Bridging the Annotation-Retrieval Gap in Image Search. IEEE Multimedia (July-September, 2007)
Djeraba, C.: Association and Content-Based Retrieval. IEEE Tran. Knowledge and Data Engineering 15(1) (2003)
Fasel, B., Luettin, J.: Automatic Facial Expression Analysis: A Survey. Pattern Recognition 36(3) (2003)
Han, J., Kamber, M.: Data Mining, Concepts and Techniques. Morgan Kaufmann, San Francisco (2006)
Ito, H., Koshimizu, H.: Some Experiments of Face Annotation Based on Latent Semantic Indexing in FIARS. In: Gabrys, B., Howlett, R.J., Jain, L.C. (eds.) KES 2006. LNCS (LNAI), vol. 4252, pp. 1208–1215. Springer, Heidelberg (2006)
Kontostathis, A., Pottenger, W.M.: A Framework for Understanding Latent Semantic Indexing (LSI) Performance. Inform. Processing & Management 42 (2006)
Li, J., Wang, J.Z.: Real-Time Computerized Annotation of Pictures. IEEE Tran. PAMI (to appear, 2007)
Monay, F., Gatica-Perez, D.: Modeling Semantic Aspects for Cross-Media Image Indexing. IEEE Tran. PAMI 29(10) (2007)
Pantic, M., Rothkrantz, L.J.M.: Facial Action Recognition for Facial Expression Analysis From Static Face Images. IEEE Tran. SMC - Part B 34(3) (2004)
Skillicorn, D.: Understanding Complex Datasets. Data Mining with Matrix Decompositions. Chapman & Hall/CRC, Boca Raton (2007)
Softopia Japan Foundation: Face Image database, http://www.hoip.jp/web=catalog/top.html
Zhao, R., Grosky, W.I.: Narrowing the Semantic Gap? Improved Text-Based Web Document Retrieval Using Visual Features. IEEE Trans. on Multimedia 4(2) (2002)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ito, H., Kawai, Y., Koshimizu, H. (2008). Face Image Annotation Based on Latent Semantic Space and Rules. In: Lovrek, I., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2008. Lecture Notes in Computer Science(), vol 5178. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85565-1_95
Download citation
DOI: https://doi.org/10.1007/978-3-540-85565-1_95
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-85564-4
Online ISBN: 978-3-540-85565-1
eBook Packages: Computer ScienceComputer Science (R0)