8 March 1999 Depth-based selective image reconstruction using spatiotemporal image analysis
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In industrial plants, a remote monitoring system which removes physical tour inspection is often considered desirable. However the image sequence given from the mobile inspection robot is hard to see because interested objects are often partially occluded by obstacles such as pillars or fences. Our aim is to improve the image sequence that increases the efficiency and reliability of remote visual inspection. We propose a new depth-based image processing technique, which removes the needless objects from the foreground and recovers the occluded background electronically. Our algorithm is based on spatiotemporal analysis that enables fine and dense depth estimation, depth-based precise segmentation, and accurate interpolation. We apply this technique to a real time sequence given from the mobile inspection robot. The resulted image sequence is satisfactory in that the operator can make correct visual inspection with less fatigue.
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Tetsuji Haga, Kazuhiko Sumi, Manabu Hashimoto, Akinobu Seki, "Depth-based selective image reconstruction using spatiotemporal image analysis", Proc. SPIE 3640, Three-Dimensional Image Capture and Applications II, (8 March 1999); doi: 10.1117/12.341063; https://doi.org/10.1117/12.341063

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