| Summary: | 碩士 === 國立雲林科技大學 === 電子工程系 === 103 === The 3D filming system can be divided into two methods: array cameras and depth cameras. With these cameras, the 3D video can be produced, and the stereoscopic display is combined for playing videos. Planar videos that apply other filming methods have to go through the post conversion technology to produce stereoscopic depth, and the Depth Image Based Rendering (DIBR) is applied to generate left and right perspectives. Finally, the videos are played with stereoscopic display. Since the source of 3D filming is more expensive and planar videos are common video types, to develop a 2D to 3D conversion technology can solve the problem of insufficient 3D contents. In addition, the costs of 3D content production are lower and more flexible.
This paper applies automatic depth estimation method to develop the 2D to 3D video conversion technology. With the Depth Image Based Rendering (DIBR), the left and right perspectives are generated, and the videos are played with stereoscopic display. This paper will automatically adjust the required threshold for establishing video groups according to the RGB distribution of source images, and determine that if the video contents have to adjust to extend the depth information according to the change of RGB distribution under the timeline. In addition, this paper also uses the type of the movement amount of an image to modify redundant movement amount and applies the feature of object movement in front of cameras to establish the object depth. Moreover, this paper uses video groups to calculate the texture features and determines the depth directions of atmospheric perspective, particular condition, and linear perspective. The above depth information is integrated with the movement trajectory, which can emphasize the object depth and suppress wrong depth at the same time to establish the stereoscopic depth.
The proposed 2D to 3D video conversion technology can establish the stereoscopic depth in different videos flexibly as well as establish the outline of stereoscopic depth accurately. This paper can solve the problem that the current 2D to 3D video conversion technologies cannot emphasize the 3D features and maintain low beating of 3D videos at the same time. Finally, the p-thread and the CUDA multi-core are applied to accelerate the proposed adaptive 2D to 3D depth estimation algorithm, which makes the video conversion update rate of 1080P can achieve over 15fps.
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