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http://hdl.handle.net/10397/105644
Title: | Learning dynamic guidance for depth image enhancement | Authors: | Gu, S Zuo, W Guo, S Chen, Y Chen, C Zhang, L |
Issue Date: | 2017 | Source: | 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 21-26 July 2017, Honolulu, Hawaii, p. 712-721 | Abstract: | The depth images acquired by consumer depth sensors (e.g., Kinect and ToF) usually are of low resolution and insufficient quality. One natural solution is to incorporate with high resolution RGB camera for exploiting their statistical correlation. However, most existing methods are intuitive and limited in characterizing the complex and dynamic dependency between intensity and depth images. To address these limitations, we propose a weighted analysis representation model for guided depth image enhancement, which advances the conventional methods in two aspects: (i) task driven learning and (ii) dynamic guidance. First, we generalize the analysis representation model by including a guided weight function for dependency modeling. And the task-driven learning formulation is introduced to obtain the optimized guidance tailored to specific enhancement task. Second, the depth image is gradually enhanced along with the iterations, and thus the guidance should also be dynamically adjusted to account for the updating of depth image. To this end, stage-wise parameters are learned for dynamic guidance. Experiments on guided depth image upsampling and noisy depth image restoration validate the effectiveness of our method. | Publisher: | Institute of Electrical and Electronics Engineers | ISBN: | 978-1-5386-0457-1 (Electronic) 978-1-5386-0458-8 (Print on Demand(PoD)) |
DOI: | 10.1109/CVPR.2017.83 | Rights: | © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The following publication S. Gu, W. Zuo, S. Guo, Y. Chen, C. Chen and L. Zhang, "Learning Dynamic Guidance for Depth Image Enhancement," 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI, USA, 2017, pp. 712-721 is available at https://doi.org/10.1109/CVPR.2017.83. |
Appears in Collections: | Conference Paper |
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Gu_Learning_Dynamic_Guidance.pdf | Pre-Published version | 5.53 MB | Adobe PDF | View/Open |
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