Multiple perspective interactive video

  • Authors:

  • Arun Katkere;Don Kuramura;Saied Moezzi;Patrick Kelly;Deborah Swanberg;Koji Wakimoto;Edward Hunter;Li-Cheng Tai;Shankar Chatterjee;Ramesh Jain

  • Affiliations:

  • Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA;Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA;Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA;Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA;Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA;Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA;Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA;Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA;Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA;Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA

  • Venue:
  • IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
  • Year:
  • 1995

Quantified Score

Hi-index 0.02

Visualization

Abstract

Crucial to the transformation of computers into intelligent multimedia systems is the ability to access, manipulate and manage visual information. In particular, video data is becoming a prevalent source of such information. Our Multiple Perspective Interactive Video (MPI-Video), project integrates a variety of visual computing operations with modeling and interaction techniques, to extract, synthesize and manage dynamic representations of scenes observed from multiple perspectives. Automatic and semi-automatic analysis of video data from multiple cameras is performed. This analysis is used to build a three-dimensional model of the environment monitored by the cameras. MPI- Video has applications in a variety of areas including the development of immersive video for telepresence systems, traffic monitoring and control and the analysis of physical performances, e.g. sports and dance. This video presents an overview of MPI- Video along with demonstrations of two MPI-Video prototypes developed in the Visual Computing Lab. Further details on MPI- Video are described by Jain and Wakimoto in [Jain and Wakimoto, 1995] and in our technical report [Kelly et al., 1995]