%0 Journal Article %1 Sudhir1996354 %A Sudhir, G. %A Lee, John C.M. %D 1996 %J Journal of Visual Communication and Image Representation %K motion_analysis of_applications %N 4 %P 354 - 368 %R http://dx.doi.org/10.1006/jvci.1996.0031 %T Video Annotation by Motion Interpretation Using Optical Flow Streams %U http://www.sciencedirect.com/science/article/pii/S1047320396900310 %V 7 %X A new approach to automatic annotation of video sequences by dominant camera motion interpretation is presented. Unlike other approaches, we separate the optical flow into two categories—singularandnon-singular—which, as we show, is a more natural way of classification for the purpose ofdominantcamera motion interpretation. We show that identification of patterns created by such natural categories, which can be observed from themeasuredoptical flow, can help focus the interpretation ofdominantcamera motion in video segments. For robust detection of such natural patterns, we propose the computation of optical flow streams (OFS) from the video data and analyze the ØFS\ for the extraction of dominant motion content in the video segments. The advantage of the proposed approach is its robustness in the extraction of dominant motion content in a video segment. We demonstrate this on a variety of real video sequences by generating the automatic motion annotation of the video frames and comparing it with manual motion annotation.

@article{Sudhir1996354, abstract = {A new approach to automatic annotation of video sequences by dominant camera motion interpretation is presented. Unlike other approaches, we separate the optical flow into two categories—singularandnon-singular—which, as we show, is a more natural way of classification for the purpose ofdominantcamera motion interpretation. We show that identification of patterns created by such natural categories, which can be observed from themeasuredoptical flow, can help focus the interpretation ofdominantcamera motion in video segments. For robust detection of such natural patterns, we propose the computation of optical flow streams (OFS) from the video data and analyze the \{OFS\} for the extraction of dominant motion content in the video segments. The advantage of the proposed approach is its robustness in the extraction of dominant motion content in a video segment. We demonstrate this on a variety of real video sequences by generating the automatic motion annotation of the video frames and comparing it with manual motion annotation. }, added-at = {2014-10-01T16:08:20.000+0200}, author = {Sudhir, G. and Lee, John C.M.}, biburl = {https://www.bibsonomy.org/bibtex/24c425a076f5b97ce3949c75c1b02946c/alex_ruff}, description = {Video Annotation by Motion Interpretation Using Optical Flow Streams}, doi = {http://dx.doi.org/10.1006/jvci.1996.0031}, interhash = {91f2b261e23d60a04c27ec0651691b1e}, intrahash = {4c425a076f5b97ce3949c75c1b02946c}, issn = {1047-3203}, journal = {Journal of Visual Communication and Image Representation }, keywords = {motion_analysis of_applications}, number = 4, pages = {354 - 368}, timestamp = {2014-10-01T16:08:20.000+0200}, title = {Video Annotation by Motion Interpretation Using Optical Flow Streams }, url = {http://www.sciencedirect.com/science/article/pii/S1047320396900310}, volume = 7, year = 1996 }