Personalized production of basketball videos from multi-sensored data under limited display resolution
Integration of information from multiple cameras is essential in television production or intelligent surveillance systems. We propose an autonomous system for personalized production of basketball videos from multi-sensored data under limited display resolution. The problem consists in selecting the right view to display among the multiple video streams captured by the investigated camera network. A view is defined by the camera index and the parameters of the image cropped within the selected camera. We propose criteria for optimal planning of viewpoint coverage and camera selection. Perceptual comfort is discussed as well as efficient integration of contextual information, which is implemented by smoothing generated viewpoint/camera sequences to alleviate flickering visual artifacts and discontinuous story-telling artifacts. We design and implement the estimation process and verify it by experiments, which shows that our method efficiently reduces those artifacts.
content repurposing multi-sensored data fusion autonomous content production