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A Novel 2D-to-3D Video Conversion Method Using Time-Coherent Depth Maps.

Yin S, Dong H, Jiang G, Liu L, Wei S - Sensors (Basel) (2015)

Bottom Line: In this paper, we propose a novel 2D-to-3D video conversion method for 3D entertainment applications. 3D entertainment is getting more and more popular and can be found in many contexts, such as TV and home gaming equipment. 3D image sensors are a new method to produce stereoscopic video content conveniently and at a low cost, and can thus meet the urgent demand for 3D videos in the 3D entertaiment market.Global depth gradient is computed according to image type while local depth refinement is related to color information.The experimental results prove that this novel method can adapt to different image types, reduce computational complexity and improve the temporal smoothness of generated 3D video.

View Article: PubMed Central - PubMed

Affiliation: Institute of Microelectronics, Tsinghua University, Beijing 100084, China. yinsy@tsinghua.edu.cn.

ABSTRACT
In this paper, we propose a novel 2D-to-3D video conversion method for 3D entertainment applications. 3D entertainment is getting more and more popular and can be found in many contexts, such as TV and home gaming equipment. 3D image sensors are a new method to produce stereoscopic video content conveniently and at a low cost, and can thus meet the urgent demand for 3D videos in the 3D entertaiment market. Generally, 2D image sensor and 2D-to-3D conversion chip can compose a 3D image sensor. Our study presents a novel 2D-to-3D video conversion algorithm which can be adopted in a 3D image sensor. In our algorithm, a depth map is generated by combining global depth gradient and local depth refinement for each frame of 2D video input. Global depth gradient is computed according to image type while local depth refinement is related to color information. As input 2D video content consists of a number of video shots, the proposed algorithm reuses the global depth gradient of frames within the same video shot to generate time-coherent depth maps. The experimental results prove that this novel method can adapt to different image types, reduce computational complexity and improve the temporal smoothness of generated 3D video.

No MeSH data available.


The similarity values of the global depth gradient calculated in the new video shot frame and the global depth gradients in frames with a video shot under tolerant value 10.
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sensors-15-15246-f015: The similarity values of the global depth gradient calculated in the new video shot frame and the global depth gradients in frames with a video shot under tolerant value 10.

Mentions: Figure 15 and Figure 16 show that the similarity values of the global depth gradient calculated in the new video shot frame and the global depth gradients in frames with a video shot under tolerant values 10 and 15 respectively. The horizontal axis is the frame number within the same video shot and the vertical axis is the similarity value.


A Novel 2D-to-3D Video Conversion Method Using Time-Coherent Depth Maps.

Yin S, Dong H, Jiang G, Liu L, Wei S - Sensors (Basel) (2015)

The similarity values of the global depth gradient calculated in the new video shot frame and the global depth gradients in frames with a video shot under tolerant value 10.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4541829&req=5

sensors-15-15246-f015: The similarity values of the global depth gradient calculated in the new video shot frame and the global depth gradients in frames with a video shot under tolerant value 10.
Mentions: Figure 15 and Figure 16 show that the similarity values of the global depth gradient calculated in the new video shot frame and the global depth gradients in frames with a video shot under tolerant values 10 and 15 respectively. The horizontal axis is the frame number within the same video shot and the vertical axis is the similarity value.

Bottom Line: In this paper, we propose a novel 2D-to-3D video conversion method for 3D entertainment applications. 3D entertainment is getting more and more popular and can be found in many contexts, such as TV and home gaming equipment. 3D image sensors are a new method to produce stereoscopic video content conveniently and at a low cost, and can thus meet the urgent demand for 3D videos in the 3D entertaiment market.Global depth gradient is computed according to image type while local depth refinement is related to color information.The experimental results prove that this novel method can adapt to different image types, reduce computational complexity and improve the temporal smoothness of generated 3D video.

View Article: PubMed Central - PubMed

Affiliation: Institute of Microelectronics, Tsinghua University, Beijing 100084, China. yinsy@tsinghua.edu.cn.

ABSTRACT
In this paper, we propose a novel 2D-to-3D video conversion method for 3D entertainment applications. 3D entertainment is getting more and more popular and can be found in many contexts, such as TV and home gaming equipment. 3D image sensors are a new method to produce stereoscopic video content conveniently and at a low cost, and can thus meet the urgent demand for 3D videos in the 3D entertaiment market. Generally, 2D image sensor and 2D-to-3D conversion chip can compose a 3D image sensor. Our study presents a novel 2D-to-3D video conversion algorithm which can be adopted in a 3D image sensor. In our algorithm, a depth map is generated by combining global depth gradient and local depth refinement for each frame of 2D video input. Global depth gradient is computed according to image type while local depth refinement is related to color information. As input 2D video content consists of a number of video shots, the proposed algorithm reuses the global depth gradient of frames within the same video shot to generate time-coherent depth maps. The experimental results prove that this novel method can adapt to different image types, reduce computational complexity and improve the temporal smoothness of generated 3D video.

No MeSH data available.