场景理解:一瞥世界的调查

Prajakta Pawar, V. Devendran
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引用次数: 4

摘要

人类在视觉上对自然场景的感知和对高水平场景结构的理解是非常熟练的。近年来,场景理解是计算机视觉中最具挑战性和最重要的问题。图像是视觉的,但视觉信息可以具有各种特征,如形状、边缘、纹理和颜色。物体检测背后的主要目标是识别图像中存在的所有物体以及它们的位置。对场景的理解整合了多个层次的有意义信息,以提取语义关系和模式。各种物体之间的相互作用对人类来说是最直观、最自然的。与物体识别相比,场景理解识别的是物体的目标以及目标在场景中的分布。场景理解在计算机视觉中对视觉场景的感知、分析和解释有着重要的影响,并导致了新的研究领域。本文综述了场景理解的概念,包括特征提取、分类和场景识别以及相关的数据集。最后,我们总结了一些目标检测尚未解决的挑战,这些挑战可以作为进一步研究的范围。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Scene Understanding: A Survey to See the World at a Single Glance
Humans are extremely proficient at visually perceiving natural scenes and understanding high level scene structures. In recent times, scene understanding is a challenging and most important problem in computer vision. Images are visual, however the visual information can be with various features like shape, edges, texture and color. The main objective behind object detection is to identify what are all objects present in an image and where they all located. Understanding a scene integrates meaningful information at multiple levels to extract semantic relationships and patterns. The interaction between various objects is most intuitive and natural to human being. As compared with object recognition, scene understanding identify the target of objects and also the distribution of targets in a scene. Scene understanding have a significant impact in computer vision to perceive, analyze, and interpret the visual scenes which leads to new research areas. In this paper, we review the scene understanding concept including feature extraction, classification and scene recognition and related datasets. At last, we have concluded some challenges of object detection remain unsolved and can be scope for further research work.
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