How Far 3D Shapes Can Be Understood from 2D Silhouettes
IEEE Transactions on Pattern Analysis and Machine Intelligence
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
Live Mixed-Reality 3D Video in Soccer Stadium
ISMAR '03 Proceedings of the 2nd IEEE/ACM International Symposium on Mixed and Augmented Reality
Synthesizing Free-Viewpoint Images from Multiple View Videos in Soccer Stadium
CGIV '06 Proceedings of the International Conference on Computer Graphics, Imaging and Visualisation
Free viewpoint video generation for walk-through experience using image-based rendering
MM '08 Proceedings of the 16th ACM international conference on Multimedia
SURF: speeded up robust features
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Virtual Viewpoint Replay for a Soccer Match by View Interpolation From Multiple Cameras
IEEE Transactions on Multimedia
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In this paper, we propose a dynamic camera calibration and object extraction method for sport videos captured with a moving pan-tilt-zoom camera. Such technology realizes an immersive free-viewpoint experience whereby audiences can see real sport scenes from any viewpoint. Camera calibration and object extraction are two of the most important processes for rendering free-viewpoint video, since a 3-dimensional model of each object needs to be reconstructed in every frame based on objects' textures and camera parameters. Most conventional rendering methods only use static cameras whose camera parameters and background models change little. However, since the cameras have to be set apart widely enough to capture the entire scene, the resolution of each object becomes low and is not sufficient for rendering high-quality free-viewpoint video. In order to obtain the texture of an object in high resolution from a moving pan-tilt-zoom camera, our proposed method estimates camera parameters by identifying reliable corresponding feature points between video frames, and also extracts the precise textures of objects using estimated camera parameters. Experimental results revealed that the proposed method successfully estimated precise camera parameters compared to the conventional method. Furthermore, by applying our proposed approach, the free-viewpoint video was rendered without visual defects.