结合深度信息在室内环境中寻找目标

Yongqiang Gao, Jianhua Zhang, Liwei Zhang, Ying Hu, Jianwei Zhang
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引用次数: 4

摘要

检测和定位场景中的物体是许多计算机视觉任务的重要步骤。在检测和定位特定于类别的对象方面已经做了很多工作。然而,对于比特定类别对象检测更常见、更重要的通用对象度量的研究却很少。本文在现有方法的基础上,结合深度信息这一新的线索,提出了一种新的室内场景中一般物体的检测和定位方法。通过实验,我们发现通过添加深度信息线索,检测和定位的性能会比原来的方法更好(特别是对于封闭物体)。最后,介绍了一种选择包含可能目标的边界框的方法,并通过实验证明了该方法的有效性。
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Finding objects at indoor environment combined with depth information
To detect and localize objects in a scene is an essential step for many computer vision tasks. Many efforts have been done for detecting and localizing category-specific ojects. However, only few works focused on the generic objectness measure which is more common and important than category-specific object detection. Base on an existing method, in this paper, a novel method by combining a new cue, the depth information, is proposed for detecting and localizing generic objects in the indoor scenes. Through our experiments, we found that by adding depth information cue the performance of detecting and localizing will be better (especially for the closed objects) than the original method. Finally, a method for selecting bounding box which contains a possible object is also introduced and the result is promising by being shown in our experiments.
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