Abstract
In this paper we present a real-time scan-line segment based stereo vision for the estimation of biologically motivated classifier cells in an active vision system. The system is challenged to overcome several problems in autonomous mobile robotic vision such as the detection of incoming moving objects and estimating its 3D motion parameters in a dynamic environment. The proposed algorithm employs a modified optimization module within the scan-line framework to achieve valuable reduction in computation time needed for generating real-time depth map. Moreover, the experimental results showed high robustness against noises and unbalanced light condition in input data.
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Shafik, M.S.E.N., Mertsching, B. (2009). Real-Time Scan-Line Segment Based Stereo Vision for the Estimation of Biologically Motivated Classifier Cells. In: Mertsching, B., Hund, M., Aziz, Z. (eds) KI 2009: Advances in Artificial Intelligence. KI 2009. Lecture Notes in Computer Science(), vol 5803. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04617-9_12
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DOI: https://doi.org/10.1007/978-3-642-04617-9_12
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