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Two-wheeler Detection using the Local Uniform Projection Vector based on Curvature Feature
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 Title & Authors
Two-wheeler Detection using the Local Uniform Projection Vector based on Curvature Feature
Lee, Yeunghak; Kim, Taesun; Shim, Jaechang;
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Recent research has been devoted and focused on detecting pedestrian and vehicle in intelligent vehicles except for the vulnerable road user(VRUS). In this paper suggest a new projection method which has robustness for rotation invariant and reducing dimensionality for each cell from original image to detect two-wheeler. We applied new weighting values which are calculated by maximum curvature containing very important object shape features and uniform local binary pattern to remove the noise. This paper considered the Adaboost algorithm to make a strong classification from weak classification. Experiment results show that the new approach gives higher detection accuracy than of the conventional method.
Two-wheeler;Curvature;Adaboost;Projection;Local Binary Pattern;
 Cited by
M. Pedersoli, J. Gonzalez, X. Hu, and X. Roca, "Toward Real-Time Pedestrian Detection Based on a Deformable Template Model," Intelligent Transportation Systems, Vol. 15, No. 1, pp. 355-364, 2014. crossref(new window)

H. Jung, Y. Ehara, J. K. Tan, H. Kim, and S. Ishikawa, "Applying MSC-HOG Feature to the Detection of a Human on a Bicycle," Proceeding of 12'th International Conference on Control, Automation and Systems, pp. 514-517, 2012.

H. Cho, P.E Rybski, and W. Zhang, "Visionbased Bicyclist Detection and Tracking for Intelligent Vehicles," Proceeding of IEEE Intelligent Vehicles Symposium, pp. 454-461, 2010.

N. Dalal and B. Triggs, "Histogram of Oriented Gradients for Human Detection," Proceeding of Computer Vision and Pattern Recognition, pp. 886-893, 2005.

T. Watanabe, S. Ito, and K. Yokoi, "Co-occurrence Histogram of Oriented Gradients for Detection," Advances in Image and Video Technology, Vol. 5414, pp. 37-47, 2009. crossref(new window)

X. Y. Wang, T. X. Han, and S. Yan, "An HOG-LBP Human Detector with Partial Occlusion Handling," Proceeding of International Conference on Computer Vision, pp. 32-39, 2009.

T. Ojala, M. Pietikainnen, and D. Harwood, "A Comparative Study of Texture Measures with Classification based on Features Distribution," Pattern Recognition, Vol. 29, No. 1, pp. 51-59, 1996. crossref(new window)

A. Haldou, X. You, and B. Bogno, "Pedestrian Detection based on Multi-Block Local Binary Pattern and Biologically Inspired Feature," Computer and Information Science, Vol. 7, No. 1, pp. 125-134, 2014.

S. Pavani, D. Delgado, and A. F. Frangi, “Haar-like Features with Optionally Weighted Rectangles for Rapid Object Detection,” Pattern Recognition, Vol. 43, No. 1, pp.1 60-172, 2010. crossref(new window)

C. Papageorgiou and T. Poggio, "A Trainable System for Object Detection," International Journal of Computer Vision, Vol. 38, No. 1, pp. 15-33, 2000. crossref(new window)

Y. H. Lee, J. Y. Ko, S. H. Yoon, T. M. Rho, and J. C. Shim, “Pedestrian Recognition using Adaboost Algorithm based on Cascade Method by Curvature and HOG," Journal of Korean Institute of Information Scientists and Engineers, Vol. 16, No. 6, pp. 654-662, 2010.

Y. H. Lee and D. Marshall, "Curvature based Normalized 3D Component Facial Image Recognition using Fuzzy Integral," Applied Mathematics and Computation, Vol. 205, No. 2, pp. 815-823, 2008. crossref(new window)

F.G. Peet and T.S. Sahota, "Surface Curvature as a Measure of Image Texture," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 7, No. 6, pp. 734-738, 1985. crossref(new window)

S. Umbaugh, Computer Vision and Image Processing:A Practical Approach using CVIPtools, Prentice Hall PTR, Upper Saddle River, New Jersey, 1998.

Receiver operating Characteristic, (accessed August 5, 2015).

Y. Lee, T. Kim, S. Lee, and J. C. Shim, "New Approach to Two Wheelers Detection using Cell Comparison," Journal of Multimedia Information System, Vol. 1, No. 1, pp. 45-53, 2014.

T. Li, X. Cao and Y. Xu, "An Effective Crossing Cyclist Detection on a Moving Vehicle," Proceedings of the 8th World Congress on Intelligent Control and Automation, pp. 368-372, 2010.

Y. H. Lee, J. C. Shim, and T. H. Yi, "3D Face Recognition using Projection Vectors for the Area in Contour Lines," The Journal of Korea Multimedia Society, Vol. 6, No. 2, pp.230-239, 2003.