Abstract
Background Subtraction is an important preprocessing step for extracting the features of tracking objects in the vision-based HCI system. In this paper, the orientation histogram between the foreground image and the background image is compared to extract the foreground probability in the local area. The orientation histogram-based method is partially robust against illumination change and small moving objects in background. There are two major drawbacks of using histograms which are quantization errors in histogram binning and slow computation speed. With Gaussian binning and integral histogram, we present the recursive partitioning method that gives false detection suppression and fast computation speed.
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Jang, D., Jin, X., Choi, Y., Kim, T. (2008). Background Subtraction Based on Local Orientation Histogram. In: Lee, S., Choo, H., Ha, S., Shin, I.C. (eds) Computer-Human Interaction. APCHI 2008. Lecture Notes in Computer Science, vol 5068. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70585-7_25
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DOI: https://doi.org/10.1007/978-3-540-70585-7_25
Publisher Name: Springer, Berlin, Heidelberg
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