三维空间中基于原目标显著性的计算立体视觉模型

2018 IEEE Biomedical Circuits and Systems Conference (BioCAS) Pub Date : 2018-10-01 DOI:10.1109/BIOCAS.2018.8584679

Elena Mancinelli, E. Niebur, R. Etienne-Cummings

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引用次数: 3

摘要

我们的视觉系统处理三维空间，但目前大多数显著性模型不包括深度信息。我们扩展了基于原型对象的模型，以显示立体深度感知如何改变预测自然场景显著性的能力。结果表明，该方法能够标记深度不连续，并且在统计上有很大的改进。

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Computational stereo-vision model of proto-object based saliency in three-dimensional space

Our visual system deals with a three-dimensional space but most of the current saliency models do not include depth information. We extend a proto-object based model to show how stereoscopic depth perception changes the ability to predict saliency on natural scenes. Results show the ability to mark depth discontinuities and a promising statistical improvement.

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来源期刊

2018 IEEE Biomedical Circuits and Systems Conference (BioCAS)

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