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14 December 2015 Contour detection combined with depth information
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Proceedings Volume 9813, MIPPR 2015: Pattern Recognition and Computer Vision; 98130I (2015) https://doi.org/10.1117/12.2205466
Event: Ninth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2015), 2015, Enshi, China
Abstract
Many challenging computer vision problems have been proven to benefit from the incorporation of depth information, to name a few, semantic labellings, pose estimations and even contour detection. Different objects have different depths from a single monocular image. The depth information of one object is coherent and the depth information of different objects may vary discontinuously. Meanwhile, there exists a broad non-classical receptive field (NCRF) outside the classical receptive field (CRF). The response of the central neuron is affected not only by the stimulus inside the CRF, but also modulated by the stimulus surrounding it. The contextual modulation is mediated by horizontal connections across the visual cortex. Based on the findings and researches, a biological-inspired contour detection model which combined with depth information is proposed in this paper.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jie Xiao and Chao Cai "Contour detection combined with depth information", Proc. SPIE 9813, MIPPR 2015: Pattern Recognition and Computer Vision, 98130I (14 December 2015); https://doi.org/10.1117/12.2205466
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