Abstract
Location of human features, such as human eye centers, is much important for face image analysis and understanding. This paper proposes a context-based method for human eye centers search. A neural network learns the contexts between human eye centers and their environment in images. For some initial positions, the distances between them and the labeled eye centers in horizontal and vertical directions are learned and remembered respectively. Given a new initial position, the system will predict the eye centers’ positions according to the contexts that the neural network learned. Two experiments on human eye centers search showed promising results.
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References
Feng, G., Yuen, P.: Variance Projection Function and Its Application to Eye Detection for Human Face Recognition. Pattern Recognition Letters 19, 899–906 (1998)
Zhou, Z., Geng, X.: Projection Functions for Eye Detection. Pattern Recognition (2004)
Huang, W., Yin, B., Jiang, C., Miao, J.: A New Approach for Eye Feature Extraction Using 3D Eye Template. In: Proc. International Symposium on intelligent Multimedia, Video and Speech Processing (2001)
Yuille, A.: Deformable Templates for Face Detection. Journal of Cognitive Neuroscience 3, 59–70 (1991)
Huang, C.L., Chen, C.W.: Human Face Feature Extraction for Face Interpretation and Recognition. Pattern recognition 25, 1435–1444 (1996)
Lam, K., Yan, H.: Locating and Extracting the Eye in Human Face Images. Pattern Recognition 29, 771–779 (1996)
Deng, J.Y., Lai, F.: Region-based Template Deformation and Masking for Eye-Feature Extraction and Description. Pattern recognition 30, 403–419 (1997)
Jeng, S.H., Liao, H.: Facial Feature Detection Using Geometrical Face Model: An Efficient Approach. Pattern Recognition 31, 273–282 (1998)
Cootes, T.F., Taylor, C.J., Cooper, J.: Active Shape Models - Their Training and Application. Computer Vision and Image Understanding 61, 38–59 (1995)
Cootes, T.F., Edwards, G.J., Taylor, C.J.: Active Appearance Models. In: Burkhardt, H., Neumann, B. (eds.) ECCV 1998. LNCS, vol. 1407, pp. 484–498. Springer, Heidelberg (1998)
Jesorsky, O., Kirchberg, K., Frischholz, R.: Robust Face Detection Using The Hausdorff Distance. In: Proc. The 3rd International Conference on Audio and Video-Based Biometric Person Authentication, pp. 91–95 (2001)
Niu, Z., Shan, S., Yan, S., Chen, X., Gao, W.: 2D Cascaded AdaBoost for Eye Localization. In: Proc. International Conference on Pattern Recognition, vol. 2, pp. 1216–1219 (2006)
Kruppa, H., Santana, M., Schiele, B.: Fast and Robust Face Finding via Local Context. In: Proc. Joint IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance (VS-PETS’03), Nice, France (2003)
Paletta, L., Greindl, C.: Context Based Object Detection From Video. In: Crowley, J.L., Piater, J.H., Vincze, M., Paletta, L. (eds.) ICVS 2003. LNCS, vol. 2626, pp. 502–512. Springer, Heidelberg (2003)
Strat, T.M., Fischler, M.A.: Context-based Vision: Recognizing Objects Using Information From Both 2D and 3D Imagery. IEEE-PAMI 13, 1050–1065 (1991)
Torralba, A., Sinha, P.: Statistical Context Priming for Object Detection. In: Proc. IEEE International Confernce on Computer Vision (2001)
Torralba, A.: Modeling Global Scene Factors in Attention. Journal of Optical Society of America A (Special Issue on Bayesian and Statistical Approaches to Vision) 20, 1407–1418 (2003)
Torralba, A., Murphy, K.P., Freeman, W.T.: Contextual Models for Object Detection using Boosted Random Fields. Advance in Neural Information Processing Systems (2004)
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Miao, J., Qing, L., Duan, L., Gao, W. (2007). Searching Eye Centers Using a Context-Based Neural Network. In: Liu, D., Fei, S., Hou, Z., Zhang, H., Sun, C. (eds) Advances in Neural Networks – ISNN 2007. ISNN 2007. Lecture Notes in Computer Science, vol 4492. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72393-6_102
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DOI: https://doi.org/10.1007/978-3-540-72393-6_102
Publisher Name: Springer, Berlin, Heidelberg
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