A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
A spatio-temporal auto regressive model for frame rate upconversion
IEEE Transactions on Circuits and Systems for Video Technology
Spatial-Temporal Fusion for High Accuracy Depth Maps Using Dynamic MRFs
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fusion of range and color images for denoising and resolution enhancement with a non-local filter
Computer Vision and Image Understanding
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part I
Image Interpolation by Adaptive 2-D Autoregressive Modeling and Soft-Decision Estimation
IEEE Transactions on Image Processing
Depth Video Enhancement Based on Weighted Mode Filtering
IEEE Transactions on Image Processing
High quality depth map upsampling for 3D-TOF cameras
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
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This paper proposes an adaptive color-guided auto-regressive (AR) model for high quality depth recovery from low quality measurements captured by depth cameras. We formulate the depth recovery task into a minimization of AR prediction errors subject to measurement consistency. The AR predictor for each pixel is constructed according to both the local correlation in the initial depth map and the nonlocal similarity in the accompanied high quality color image. Experimental results show that our method outperforms existing state-of-the-art schemes, and is versatile for both mainstream depth sensors: ToF camera and Kinect.