A Compact Representation for Compressing Converted Stereo Videos

Zhang, Zhebin; Zhou, Chen; Wang, Ronggang; Wang, Yizhou; Gao, Wen

doi:10.1109/tip.2014.2315958

Cited by 4 publications

References 33 publications

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Depth map propagation with the texture image guidance

Zhang

2014

2014 IEEE International Conference on Image Processing (ICIP)

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We propose a novel method to propagate the depth maps from key-frames to the non-key frames in a video shot. The depths of non-key frames are initialized by warping the depth maps of their corresponding key frames according to the motion estimation between them. Such initial depth maps are then refined with the guidance of their texture frames in a convex optimization process. The energy function in the optimization involves three kinds of constraints, (i) the similarity between the initial depths and the estimated ones, (ii) the spatial constraint to maintain the smoothness of homogeneous regions and region boundaries, and (iii) the temporal constraint to guarantee the temporal smoothness between adjacent frames. In the experiments, we evaluate our method on six video sequences with ground truth depth maps. The experiment results show that our method is robust to many complex scenes and obtain lower error rates of the depth propagation than the baseline method.

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Depth map propagation with the texture image guidance

Zhang

2014

2014 IEEE International Conference on Image Processing (ICIP)

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Image guided label map propagation in video sequences

Zhang

Wang

et al. 2015

2015 IEEE International Symposium on Circuits and Systems (ISCAS)

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No-Reference Quality Assessment of Stereoscopic Videos With Inter-Frame Cross on a Content-Rich Database

Yang

Zhao

Jiang

et al. 2020

IEEE Trans. Circuits Syst. Video Technol.

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With the wide application of stereoscopic video technology, the quality of stereoscopic video has attracted people's attention. Objective stereoscopic video quality assessment (SVQA) is highly challenging, but essential, particularly the noreference (NR) SVQA method, where reference information is not needed and a large number of samples are required for training and testing sets. However, as far as we know, there are only a few samples in the established stereo video database, which is unsuitable for NR quality assessment and seriously hampers the development of NR-SVQA method. For these difficulties that we encountered, we carry out a comprehensive subjective evaluation of stereoscopic video quality in our newly established TJU-SVQA databases that contain various contents, mixed resolution coding and symmetrically/asymmetrically distorted stereoscopic videos. Furthermore, we propose a new inter-frame cross map to predict the objective quality scores. We compare and analyze the performance of several state-of-the-art 2D and 3D quality evaluation methods on our new databases. The experimental results on our established databases and a public database demonstrate that the proposed method can robustly predict the quality of stereoscopic videos.

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A Compact Representation for Compressing Converted Stereo Videos

Cited by 4 publications

References 33 publications

Depth map propagation with the texture image guidance

Depth map propagation with the texture image guidance

Image guided label map propagation in video sequences

No-Reference Quality Assessment of Stereoscopic Videos With Inter-Frame Cross on a Content-Rich Database

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