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Shading cues for object class detection

机译:用于对象类别检测的阴影提示

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摘要

Recognition of object classes in natural images has made tremendous progress in recent years. Today's approaches often rely on powerful learning approaches as well as robust local 2D shape or appearance features. Exploiting 3D shape cues however has become unfashionable in recent literature. While shading cues play a major role in human perception of object shape, shape-from-shading techniques are seldom used today for object class detection. Drawing on ideas from the early days in object recognition this paper aims to revisit the concept of using shading primitives to support object class detection. We demonstrate and discuss the applicability of this approach to real world images of a standard benchmark data set. Experimental results suggest that our shading cues can be useful for object class detection.
机译:近年来,自然图像中对象类别的识别取得了巨大的进步。当今的方法通常依赖强大的学习方法以及强大的局部2D形状或外观特征。然而,在最近的文献中,利用3D形状提示已变得不流行。尽管阴影提示在人类对物体形状的感知中起着主要作用,但如今从阴影中提取形状的技术很少用于物体类别检测。本文借鉴了对象识别早期的思想,旨在重新探讨使用着色原语支持对象类检测的概念。我们演示并讨论了这种方法对标准基准数据集的真实世界图像的适用性。实验结果表明,我们的阴影提示可用于对象类别检测。

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