RGB-D datasets using microsoft kinect or similar sensors: a survey

By Ziyun Cai, Jungong Han, Li Liu, Ling Shao. 2016

145 citations recorded by the source corpus.

RGB-D data has turned out to be a very useful representation of an indoor scene for solving fundamental computer vision problems. It takes the advantages of the color image that provides appearance information of an object and also the depth image that is immune to the variations in color, illumination, rotation angle and scale. With the invention of the low-cost Microsoft Kinect sensor, which was initially used for gaming and later became a popular device for computer vision, high quality RGB-D data can be acquired easily. In recent years, more and more RGB-D image/video datasets dedicated to various applications have become available, which are of great importance to benchmark the state-of-the-art. In this paper, we systematically survey popular RGB-D datasets for different applications including object recognition, scene classification, hand gesture recognition, 3D-simultaneous localization and mapping, and pose estimation. We provide the insights into the characteristics of each important dataset, and compare the popularity and the difficulty of those datasets. Overall, the main goal of this survey is to give a comprehensive description about the available RGB-D datasets and thus to guide researchers in the selection of suitable datasets for evaluating their algorithms.

Subfields: Aerospace Engineering, Computer Vision and Pattern Recognition, Evaluation & Benchmarks, Human-Computer Interaction

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Citations in the corpus

NTU RGB+D: A Large Scale Dataset for 3D Human Activity Analysis (2016, background): “For a more extensive list of current 3D activity analysis datasets and methods, readers are referred to these survey papers [47, 1, 5, 12, 21, 45, 3].”
PKU-MMD: A Large Scale Benchmark for Continuous Multi-Modal Human Action Understanding (2017, background): “For a more extensive conclusion of activity analysis we refer to corresponding survey papers [5, 56, 1, 7].”
Elderly Fall Detection Systems: A Literature Survey (2020, background): “Work on demonstrating viability of vision-based approaches have been demonstrated which makes use of infrared cameras (Mastorakis and Makris, 2014), RGB cameras (Charﬁ et al., 2012), and RGB-D depth cameras (Cai et al., 2017).”