Abstract
Accuracy and speed are the two important keys in pedestrian detection. In order to balance these two indexes well, this thesis presents a novel pedestrian detection system, ROIs cascaded Uniform LBP and improved HOG, for real-time pedestrian detection in monocular vision. Two contributions are made in this system. First contribution is that Uniform LBP (Local Binary Pattern) cascaded improved HOG (Histograms of Oriented Gradients) are the novel structure for pedestrian detection, which can improve detection speed. Second contribution is that this pedestrian detection system is evaluated by many methods and algorithms. Experiment shows that this system can deal with 31 fps, which can be used as the real time pedestrian detection system.
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This work is supported by the National Natural Science Foundation of China (Grant: 61376028).
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Guo, A., Xu, M., Ran, F. (2016). A Novel Real-Time Pedestrian Detection System on Monocular Vision. In: Zhang, L., Song, X., Wu, Y. (eds) Theory, Methodology, Tools and Applications for Modeling and Simulation of Complex Systems. AsiaSim SCS AutumnSim 2016 2016. Communications in Computer and Information Science, vol 646. Springer, Singapore. https://doi.org/10.1007/978-981-10-2672-0_30
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DOI: https://doi.org/10.1007/978-981-10-2672-0_30
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