| 词条 | Video synopsis |
| 释义 |
Video Synopsis® is the simultaneous presentation of events that enables the review of hours of video footage in just minutes. The technology tracks and analyzes moving objects (also called events), and converts video streams into a database of objects and activities.[1] Video Synopsis has specific applications in the field of video analytics and video surveillance where, despite technological advancements and increased growth in the deployment of CCTV (closed circuit television) cameras,[2] viewing and analysis of recorded footage is still a costly and labor-intensive and time-intensive task. Technology overviewVideo Synopsis combines a visual summary of stored video together with an indexing mechanism. When a summary is required, all objects from the target period are collected and shifted in time to create a much shorter synopsis video showing maximum activity. A synopsis video clip is generated, in real time, in which objects and activities that originally occurred in different times are displayed simultaneously.[3] (See Figure 1 - Screen shots: Before and after Video Synopsis). The process begins by detecting and tracking objects of interest. Each object is represented as a tube in space-time of all video frames. Objects are detected and stored in a database in approximately real time. Following a request to summarize a time period, all objects from the desired time are extracted from the database, and indexed to create a much shorter summary video containing maximum activity. (See Figure 2 - Tube packing). Real time rendering is used to generate the summary video after object re-timing. This allows end-user control over object/event density. Video Synopsis technology was invented by Prof. Shmuel Peleg[4] of The Hebrew University of Jerusalem, Israel, and is being developed under commercial license by BriefCam, Ltd.[5] BriefCam received a license to use the technology from Yissum which is the owner of the patents registered for the technology. In May 2018, BriefCam was acquired by Japanese digital imaging giant, Canon Inc., for an estimated $90 million.[6] Investors in the company include Motorola Solutions Venture Capital, Aviv Venture Capital, and OurCrowd.[7] Recent advancesRecent advances in the field of Video Synopsis have resulted in methods that focus in collecting key-points(or frames) from the long uncut video and presenting them as a chain of key events that summarize the video. As mentioned in,[8] this is only one of the many methods employed in modern literature to perform this task. Recently, these event-driven methods have focused on correlating objects in frames, but in a more semantically related way that has been called a story-driven method of summarizing video. These methods have been shown to work well for egocentric[9] settings where the video is basically a point-of-view perspective of a single person or a group of people. See also
References1. ^Y. Pritch, S. Ratovitch, A. Hendel, and S. Peleg, Clustered Synopsis of Surveillance Video, 6th IEEE Int. Conf. on Advanced Video and Signal Based Surveillance (AVSS'09), Genoa, Italy, Sept. 2-4, 2009 2. ^Y. Pritch, A. Rav-Acha, A. Gutman, and S. Peleg, Webcam Synopsis: Peeking Around the World, ICCV'07, October 2007. 8p. 3. ^Y. Pritch, A. Rav-Acha, and S. Peleg, Nonchronological Video Synopsis and Indexing, IEEE Trans. PAMI, Vol 30, No 11, Nov. 2008, pp. 1971-1984. 4. ^A. Rav-Acha, Y. Pritch, and S. Peleg, Making a Long Video Short: Dynamic Video Synopsis, CVPR'06, June 2006, pp. 435-441. 5. ^S. Peleg, Y. Caspi, BriefCam White Paper 6. ^{{Cite web|url=https://en.globes.co.il/en/article-canon-buys-israeli-video-solutions-co-briefcai-1001235224|title=Canon buys Israeli video solutions co BriefCam for $90m|last=Yablonko|first=Yasmin|date=9 May 2018|website=Globes|language=Hebrew|archive-url=|archive-date=|dead-url=|access-date=2018-12-05}} 7. ^{{Cite web|url=https://www.cbinsights.com/company/briefcam-funding|title=BriefCam Funding & Investors - CB Insights|last=CB Insights|date=|website=www.cbinsights.com|language=en-US|archive-url=|archive-date=|dead-url=|access-date=2018-12-05}} 8. ^Muhammad Ajmal, Muhammad Husnain Ashraf, Muhammad Shakir, Yasir Abbas, Faiz Ali Shah, Video Summarization: Techniques and Classification [https://link.springer.com/chapter/10.1007%2F978-3-642-33564-8_1] 9. ^Zheng Lu, Kristen Grauman [https://www.cs.utexas.edu/~grauman/papers/lu-grauman-cvpr2013.pdf] Story-driven summarization for egocentric video. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition - 2013. Patents{{commons category|Surveillance}}
External links
3 : Image processing|Israeli inventions|Surveillance |
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