Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Graph-Based Image Segmentation
International Journal of Computer Vision
Robust Multiple Structures Estimation with J-Linkage
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Tracking planes with Time of Flight cameras and J-linkage
WACV '11 Proceedings of the 2011 IEEE Workshop on Applications of Computer Vision (WACV)
KinectFusion: real-time 3D reconstruction and interaction using a moving depth camera
Proceedings of the 24th annual ACM symposium on User interface software and technology
Blind navigation with a wearable range camera and vibrotactile helmet
MM '11 Proceedings of the 19th ACM international conference on Multimedia
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Scene analysis is an important issue in computer vision and extracting structural information is one of the fundamental techniques. Taking advantage of depth camera, we propose a novel fast plane segmentation algorithm and use it to detect obstacles in indoor environment. The proposed algorithm has two steps: the initial segmentation and the refined segmentation. Firstly, depth image is converted into 3D point cloud and divided into voxels, which are less sensitive to noises compared with pixels. Then area-growing algorithm is used to extract the candidate planes according to the normal of each voxel. Secondly, each point that hasn't been classified to any plane is examined whether it actually belongs to a plane. The two-step strategy has been proven to be a fast segmentation method with high accuracy. The experimental results demonstrate that our method can segment planes and detect obstacles in real-time with high accuracy for indoor scenes.