Abstract
Recent local state-of-the-art stereo algorithms based on variable cost aggregation strategies allow for inferring disparity maps comparable to those yielded by algorithms based on global optimization schemes. Unfortunately, thought these results are excellent, they are obtained at the expense of high computational requirements that are comparable or even higher than those required by global approaches. In this paper, we propose a cost aggregation strategy based on joint bilateral filtering and incremental calculation schemes that allow for efficient and accurate inference of disparity maps. Experimental comparison with state-of-the-art techniques shows the effectiveness of our proposal.
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Mattoccia, S., Giardino, S., Gambini, A. (2010). Accurate and Efficient Cost Aggregation Strategy for Stereo Correspondence Based on Approximated Joint Bilateral Filtering. In: Zha, H., Taniguchi, Ri., Maybank, S. (eds) Computer Vision – ACCV 2009. ACCV 2009. Lecture Notes in Computer Science, vol 5995. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12304-7_35
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DOI: https://doi.org/10.1007/978-3-642-12304-7_35
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