Semantic video analysis for psychological research on violence in computer games
Proceedings of the 6th ACM international conference on Image and video retrieval
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues
Robust Estimation of Camera Motion Using Optical Flow Models
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part I
A robust method for camera motion estimation in movies based on optical flow
International Journal of Intelligent Systems Technologies and Applications
Robust Video Content Analysis via Transductive Learning
ACM Transactions on Intelligent Systems and Technology (TIST)
Proceedings of the 22nd international workshop on Network and Operating System Support for Digital Audio and Video
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Several algorithms have been proposed to solve the problem of camera motion estimation in digital videos. However, the distinction between translation along the x-axis (y-axis) and rotation around the y-axis (x-axis) has only rarely been considered, and no approach of this kind is known to us for the MPEG domain. In this paper, we present such an algorithm for camera motion estimation in MPEG videos. For performance reasons it is reasonable to extract motion vectors directly from the compressed stream. However, since motion vectors are optimal with respect to compression, they often do not model real motion adequately and can thus be considered as "outliers" with respect to camera motion estimation. Consequently, an outlier removal algorithm is incorporated into our approach to solve this problem. Furthermore, we have investigated the minimum number of motion vectors required to obtain satisfactory results. Comprehensive experiments with 32 video clips demonstrate the performance of the proposed approach.