DocumentCode
3019907
Title
A category-level 3-D object dataset: Putting the Kinect to work
Author
Janoch, Allison ; Karayev, Sergey ; Jia, Yangqing ; Barron, Jonathan T. ; Fritz, Mario ; Saenko, Kate ; Darrell, Trevor
Author_Institution
Max-Plank-Inst. for Inf., UC Berkeley, Berkeley, Germany
fYear
2011
fDate
6-13 Nov. 2011
Firstpage
1168
Lastpage
1174
Abstract
Recent proliferation of a cheap but quality depth sensor, the Microsoft Kinect, has brought the need for a challenging category-level 3D object detection dataset to the fore. We review current 3D datasets and find them lacking in variation of scenes, categories, instances, and viewpoints. Here we present our dataset of color and depth image pairs, gathered in real domestic and office environments. It currently includes over 50 classes, with more images added continuously by a crowd-sourced collection effort. We establish baseline performance in a PASCAL VOC-style detection task, and suggest two ways that inferred world size of the object may be used to improve detection. The dataset and annotations can be downloaded at http://www.kinectdata.com.
Keywords
image colour analysis; image sensors; object detection; Microsoft Kinect; category variation; category-level 3D object detection; color image pair; crowd-sourced collection effort; depth image pair; depth sensor; instance variation; scene variation; viewpoint variation; Cameras; Detectors; Keyboards; Mice; Robot sensing systems; Shape; Three dimensional displays;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision Workshops (ICCV Workshops), 2011 IEEE International Conference on
Conference_Location
Barcelona
Print_ISBN
978-1-4673-0062-9
Type
conf
DOI
10.1109/ICCVW.2011.6130382
Filename
6130382
Link To Document