ABSTRACT
We present Videolytics, a web-based system for advanced analytics over recorded video streams. Video cameras have become widely used for indoor and outdoor surveillance. Covering even more public space in cities, the cameras serve various purposes ranging from security to traffic monitoring, urban life, and marketing. The goal is to obtain effective and efficient models to process the video data automatically and produce the desired features for data analytics. Videolytics combines the best of deep learning and hand-designed analytical models to create a solution applicable in real-life situations. The architecture of the Videolytics framework is centered around a database of video features and detected objects, where new higher-level objects result from fusion of (lower-level) objects and features already stored in the database. The system provides a number of visualization options, an SQL-based analytics module as well as a real-time surveillance mode.
- AllGoVision Video Analytics. 2021 a. https://www.govision.com/allgovision-analytics.php.Google Scholar
- PureActiv Video Analytics. 2021 b. https://www.puretechsystems.com/request-a-live-demo.Google Scholar
- J Arraiza, N Aginako, S Kioumourtzis, G Leventakis, G Stavropoulos, D Tzovaras, N Zotos, A Sideris, E Charalambous, and N Koutras. 2015. Fighting volume crime: an intelligent, scalable, and low cost approach. Journal of Polish Safety and Reliability Association, Vol. 6 (2015). http://p-react.eu/Google Scholar
- Axxonsoft. 2021. https://axxonsoft.com/intelligence/artificial_intelligence/.Google Scholar
- Johan Bissmark and Oscar Wärnling. 2017. The Sparse Data Problem Within Classification Algorithms: The Effect of Sparse Data on the Naïve Bayes Algorithm.Google Scholar
- CrowdANALYTIX. 2021. https://www.crowdanalytix.com/.Google Scholar
- Marek Dobranský. 2019. Object Detection for video surveillance using SSD approach. (2019). http://hdl.handle.net/20.500.11956/107024Google Scholar
- Marek Dobranský and Tomá vs Skopal. 2021. On Fusion of Learned and Designed Features for Video Data Analytics. In MultiMedia Modeling - 27th International Conference, MMM 2021, Prague, Czech Republic, June 22-24, 2021, Proceedings, Part II (Lecture Notes in Computer Science, Vol. 12573). Springer, 268--280. https://doi.org/10.1007/978-3-030-67835-7_23Google Scholar
- Daniel Kang, John Emmons, Firas Abuzaid, Peter Bailis, and Matei Zaharia. 2017. NoScope: Optimizing Neural Network Queries over Video at Scale. Proc. VLDB Endow., Vol. 10, 11 (Aug. 2017), 1586--1597. https://doi.org/10.14778/3137628.3137664 Google ScholarDigital Library
- X. Li, C. X. Ling and H. Wang. 2015. The Convergence Behavior of Naive Bayes on Large Sparse Datasets. In 2015 IEEE International Conference on Data Mining. 853--858. https://doi.org/10.1109/ICDM.2015.53 Google ScholarDigital Library
- Suzanne Little, Iveel Jargalsaikhan, Kathy Clawson, Hao Li, Marcos Nieto, Cem Direkoglu, Noel E O'Connor, Alan F Smeaton, Aitor Rodriguez, Pedro Sanchez, et al. 2012. SAVASA Project@ TRECVid 2012: Interactive surveillance event detection. (2012).Google Scholar
- Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, and Alexander C Berg. 2016. Ssd: Single shot multibox detector. In European conference on computer vision. Springer, 21--37.Google ScholarCross Ref
- David Schreiber, Martin Boyer, Peter Gemeiner, and Andreas Opitz. 2019. Generic Object Detection and Tracking for Accelerating Video Analysis within VICTORIA. In 2019 International Conference on Speech Technology and Human-Computer Dialogue (SpeD). 1--6. https://www.victoria-project.eu/Google Scholar
- Senstar. 2021. https://senstar.com/products/video-analytics/.Google Scholar
- Sentinel. 2021. https://www.sentinelcv.com/.Google Scholar
- PureTech Systems. 2021. PRODUCTS: VIDEO ANALYTICS., https://www.puretechsystems.com/video-analytics.html.Google Scholar
- TimeRethink. 2021. https://timerethink.com/.Google Scholar
- Bosch Security video analytics. 2021. https://resources-boschsecurity-cdn.azureedge.net/public/documents/DS_IVA_7.10_Data_sheet_enUS_69630079883.pdf.Google Scholar
- Videolytics. 2021. http://videolytics.ms.mff.cuni.cz.Google Scholar
- Videonetics. 2021. https://www.videonetics.com/products/ai-enabled-video-analytics/.Google Scholar
Index Terms
- Videolytics: System for Data Analytics of Video Streams
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