Abstract
This paper proposes a new embedded system which can selectively detect human faces with fast speed. The embedded system is developed by using OMAP 3530 application processor which has DSP and ARM core. Since the embedded system has the limited performance of CPU and memory, we propose a hybrid system combined the YCbCr based bottom-up selective attention with the conventional Adaboost algorithm. The proposed method using the bottom-up selective attention model can reduce not only the false positive error ratio of the Adaboost based face detection algorithm but also the time complexity by finding the candidate regions of the foreground and reducing the regions of interest (ROI) in the image. The experimental results show that the implemented embedded system can successfully work for localizing human faces in real time.
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Itti, L., Koch, C., Neibur, E.: A Model of Saliency–Based Visual Attention for Rapid Scene Analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence 20(11), 1254–1259 (1998)
Koike, T., Saiki, J.: Stochastic Guided Search Model for Search Asymmetries in Visual Search Tasks. In: Bülthoff, H.H., Lee, S.-W., Poggio, T., Wallraven, C. (eds.) BMCV 2002. LNCS, vol. 2525, pp. 408–417. Springer, Heidelberg (2002); Goldstein, E.B.: Sensation and perception, 4th edn. An international Thomson publishing company, USA (1996)
Kadir, T., Brady, M.: Scale, Saliency and Image Description. Int. J. Comput. Vis. 45, 83–105 (2001); Goldstein, E.B.: Sensation and perception, 4th edn. An international Thomson publishing company, USA (1996)
Ramström, O., Christensen, H.I.: Visual Attention Using Game Theory. In: Bülthoff, H.H., Lee, S.-W., Poggio, T., Wallraven, C. (eds.) BMCV 2002. LNCS, vol. 2525, pp. 462–471. Springer, Heidelberg (2002)
Jeong, S., Ban, S.W., Lee, M.: Stereo Saliency Map Considering Affective Factors and Selective Motion Analysis in a Dynamic Environment. Neural Netw. 21, 1420–1430 (2008)
Ban, S.W., Jang, Y.M., Lee, M.: Affective Saliency Map Considering Psychological Distance. Neurocomputing 74, 1916–1925 (2011)
Viola, P., Jones, M.J.: Robust Real-Time Face Detection. International Journal of Computer Vision 57(2), 137–154 (2004)
Cerf, M., Harel, J., Einhäuser, W., Koch, C.: Predicting Human Gaze Using Low-Level Saliency Combined with Face Detection. In: Proceedings of the Twenty-First Annual Conference on Neural Information Processing Systems, NIPS 2007 (2007)
Kim, B., Ban, S.-W., Lee, M.: Improving AdaBoost Based Face Detection Using Face-Color Preferable Selective Attention. In: Fyfe, C., Kim, D., Lee, S.-Y., Yin, H. (eds.) IDEAL 2008. LNCS, vol. 5326, pp. 88–95. Springer, Heidelberg (2008)
Goldstein, E.B.: Sensation and Perception, 4th edn. International Thomson Publishing Company, USA (1996)
Park, S.J., An, K.H., Lee, M.: Saliency Map Model with Adaptive Masking Based on Independent Component Analysis. Neurocomputing 49, 417–422 (2002)
Mahmoud, T.M.: A New Fast Skin Color Detection Technique. World Academy of Science. Engineering and Technology 43, 501–505 (2008)
Bell, A.J., Sejnowski, T.J.: Edges are the Independent Components of Natural Scenes. In: NIPS, pp. 831–837 (1996)
Fröba, B., Ernst, A.: Face Detection with the Modified Census Transform. In: Proceedings of the Sixth IEEE International Conference on Automatic Face and Gesture Recognition (FGR 2004), pp. 91–96 (2004)
Texas Instruments, http://www.ti.com
ARM, http://www.arm.com/
C6EZRun Software Development Tool for TI DSP+ARM Devices
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Kim, B., Son, HM., Lee, YJ., Lee, M. (2012). Implementation of Face Selective Attention Model on an Embedded System. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds) Neural Information Processing. ICONIP 2012. Lecture Notes in Computer Science, vol 7667. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34500-5_23
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DOI: https://doi.org/10.1007/978-3-642-34500-5_23
Publisher Name: Springer, Berlin, Heidelberg
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