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M. Ivancsics, N. Brosch, M. Gelautz:
"Efficient Depth Propagation in Videos with GPU-acceleration";
Poster: IEEE Visual Communications and Image Processing (IEEE VCIP) 2014, Malta; 2014-12-07; in: "IEEE Visual Communications and Image Processing (IEEE VCIP)", (2014), 4 pages.

In this paper we propose an optimized semi-automatic approach for efficient 2D-to-3D video conversion. It is based on a conversion algorithm [1] that leverages segmentation and filtering techniques to propagate sparse depth information that was provided by a user. Our GPU acceleration of [1] significantly reduces the computation time of the original algorithm. Since the limited capacity of the GPU´s onboard memory hinders the parallel execution of large data such as videos, we additionally propose a temporally coherent clip-based 2D-to-3D conversion approach for long videos. Evaluations show that the proposed, optimized conversion approach is capable of generating high-quality results, while significantly reducing the execution time compared to the original, un-optimized approach.

In this paper we propose an optimized semi-automatic approach for efficient 2D-to-3D video conversion. It is based on a conversion algorithm [1] that leverages segmentation and filtering techniques to propagate sparse depth information that was provided by a user. Our GPU acceleration of [1] significantly reduces the computation time of the original algorithm. Since the limited capacity of the GPU´s onboard memory hinders the parallel execution of large data such as videos, we additionally propose a temporally coherent clip-based 2D-to-3D conversion approach for long videos. Evaluations show that the proposed, optimized conversion approach is capable of generating high-quality results, while significantly reducing the execution time compared to the original, un-optimized approach.