Abstract
This paper presents a method to detect adjacent multiple pedestrians using the ART2 neural network from a moving camera image. A BMA(Block Matching Algorithm) is used to obtain a motion vector from two consecutive input frames. And a frame difference image is generated by the motion compensation with the motion vector. This image is transformed into binary image by the adapted threshold and a noise is also removed. To detect multiple pedestrians, a projection histogram is processed by the shape information of human being. However, in case that pedestrians exist adjacently each other, it is very different to separate them. So, we detect adjacent multiple pedestrians using the ART2 neural network. The experimental results on our test sequences will show the high efficiency of our method.
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© 2006 Springer-Verlag Berlin Heidelberg
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Lim, JS., Lee, WB., Kim, WH. (2006). An Adjacent Multiple Pedestrians Detection Based on ART2 Neural Network. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3972. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760023_36
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DOI: https://doi.org/10.1007/11760023_36
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34437-7
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