Object recognition algorithm for mobile devices

• Autorzy: Kozik R. , Marchewka A
• Języki publikacji: EN

Abstrakty

EN

In this paper an object recognition algorithm for mobile devices is presented. The algorithm is based on a hierarchical approach for visual information coding proposed by Riesenhuber and Poggio [1] and later extended by Serre et al. [2]. The proposed method adapts an efficient algorithm to extract the information about local gradients. This allows the algorithm to approximate the behaviour of simple cells layer of Riesenhuber and Poggio model. Moreover, it is also demonstrated that the proposed algorithm can be successfully deployed on a low-cost Android smartphone.

Słowa kluczowe

EN

efficient algorithm; Android smartphone; HMAX model

• Wydawca: Instytut Telekomunikacji i Informatyki Uniwersytetu Technologiczno-Przyrodniczego w Bydgoszczy
• Czasopismo: Image Processing & Communications
• Rocznik: 2013
• Tom: Vol. 18, no. 1
• Strony: 31--36
• Opis fizyczny: Bibliogr. 11 poz., rys.

Twórcy

autor

Kozik R.

• Institute of Telecommunications, University of Technology & Life Sciences in Bydgoszcz, ul. Kaliskiego 7, 85-789 Bydgoszcz, Poland

autor

Marchewka A

• Institute of Telecommunications, University of Technology & Life Sciences in Bydgoszcz, ul. Kaliskiego 7, 85-789 Bydgoszcz, Poland

Bibliografia

• [1] M. Riesenhuber, T. Poggio, Hierarchical models of object recognition in cortex, Nat Neurosci, Vol. 2, pp.1019-1025, 1999
• [2] T. Serre, G. Kreiman, M. Kouh, C. Cadieu, U. Knoblich T. Poggio, A quantitative theory of immediate visual recognition, In:Progress in Brain Research, Computational Neuroscience: Theoretical Insights into Brain Function, Vol. 165, pp. 33-56, 2007
• [3] N. Dalal, B. Triggs, Histograms of oriented gradients for human detection, Computer Vision and Pattern Recognition, CVPR 2005, IEEE Computer Society Conference on, Vol.1, pp. 886-893, June 2005
• [4] R. Kozik, A Simplified Visual Cortex Model for Efficient Image Codding and Object Recognition, Image Processing and Communications Challenges 5, Advances in Intelligent Systems and Computing, pp. 271-278, 2013
• [5] R. Kozik, Rapid Threat Detection for Stereovision Mobility Aid System , In: T. Czachorski et al. (Eds.): Man-Machine Interactions 2, AISC 103, pp. 115-123, 2011
• [6] R. Kozik, Stereovision system for visually impaired. Burduk, Robert (ed.) et al., Computer recognition systems 4, Advances in Intelligent and Soft Computing 95, pp. 459-468, 2011
• [7] R. Kozik, A Proposal of Biologically Inspired Hi erarchical Approach to Object Recognition, Journal of Medical Informatics & Technologies, Vol. 22/2013, ISSN 1642-6037, pp. 171-176, 2013
• [8] R. Kozik, A Simplified Visual Cortex Model for Efficient Image Codding and Object Recognition, Image Processing and Communications Challenges 5, Advances in Intelligent Systems and Computing S. Choras, Ryszard, pp. 271-278, 2013
• [9] D.H. Hubel, T.N. Wiesel Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex, J Physiol, Vol. 160, pp. 106-154, 1962
• [10] J. Mutch, D.G. Lowe, Object class recognition and localization using sparse features with limited receptive fields,International Journal of Computer Vision (IJCV), Vol. 80, No. 1, pp. 45-57, October 2008
• [11] MAX pooling, http://ufldl.stanford.edu/wiki/index.php/Pooling