A New Sense for Depth of Field
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning Patterns of Activity Using Real-Time Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
Introductory Techniques for 3-D Computer Vision
Introductory Techniques for 3-D Computer Vision
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With the development of 3DTV, the conversion of existing 2D videos to 3D videos becomes an important component of 3D content production. One of the key steps in 2D to 3D conversion is how to generate a dense depth map. In this paper, we propose a novel depth extraction method based on motion and geometric information for 2D to 3D conversion, which consists of two major depth extraction modules, the depth from motion and depth from geometrical perspective. The H.264 motion estimation result is utilized and cooperates with moving object detection to diminish block effect and generates a motion-based depth map. On the other hand, a geometry-based depth map is generated by edge detection and Hough transform. Finally, the motion-based depth map and the geometry-based depth map are integrated into one depth map by a depth fusion algorithm.