{"id":7574,"date":"2019-08-12T15:37:53","date_gmt":"2019-08-12T14:37:53","guid":{"rendered":"https:\/\/citysecuritymagazine.com\/?p=7574"},"modified":"2019-08-12T16:34:05","modified_gmt":"2019-08-12T15:34:05","slug":"keeping-it-real-time-advances-in-video-analytics","status":"publish","type":"post","link":"https:\/\/citysecuritymagazine.com\/security-technology\/keeping-it-real-time-advances-in-video-analytics\/","title":{"rendered":"Advances in video analytics for CCTV"},"content":{"rendered":"

Keeping it Real-time : advances in video analytics for CCTV<\/strong><\/h1>\n

This year, it is predicted that almost a million minutes of video content will circulate the internet every single second. That is a lot of data \u2013 and a lot of potential analysis.<\/p>\n

The dramatic growth in the use of this medium is driving the demand for more efficient ways of analysing video data, particularly for CCTVs in the security industry.<\/p>\n

\u201cThere is a growing need for video analytics,\u201d explains Dr Victor Sanchez, from the University of Warwick\u2019s Department of Computer Science.<\/p>\n

Current analytics often sees a trade-off between quality and reliability on the one hand and on the other hand, computational power and storage. So, at the moment, analytics are not widely used in train stations, airports, highways, office blocks, housing developments, retail applications and distribution centres.<\/p>\n

\u201cWe wanted to investigate a solution that would help anyone looking for efficient real-time analytics. We wanted to design a tool which would provide a \u2018second set of eyes\u2019 \u2013\u00a0 a back-up for anyone with the difficult task of constantly scanning multiple, complex screens streaming security footage from a number of different positions.\u201d<\/p>\n

Machine learning<\/h4>\n

Currently, the application of deep learning analytics \u2013 where computers can predict or detect an event, based on the rules \u2018learned\u2019 from earlier data \u2013 are providing a number of solutions. These methods are either based on Convolutional Neural Networks (CNNs) or hand-crafted feature descriptors.<\/p>\n

\u201cCNNs have demonstrated outstanding performance for video analysis tasks,\u201d continues Dr Sanchez. \u201cBut these algorithms take a relatively long time to get up and running, because there are many layers to the data. It can take days or even months to train a descriptor for something like action recognition.<\/p>\n

\u201cThose methods in existence which do require shorter training and processing times, for example tools which use feature descriptors, are highly dimensional in terms of the extracted features and therefore require vast storage capacities and computational resource. This makes them expensive and\u00a0demanding systems to run.\u201d<\/p>\n

New video analytics<\/h4>\n

The research team at the University of Warwick set to work investigating a new method of feature descriptor for video analytics.<\/p>\n

\u201cWe looked at a method which encodes the motion information of a Spatio Temporal support region into a low-dimensional Binary string (STB),\u201d explains Dr Sanchez. \u201cThe encoded information for the process is obtained from two motion sources \u2013 the optical flow and the temporal gradients.<\/p>\n

\u201cUsing two motion sources provides rich motion information by considering the pixel intensity changes to create a new data space that disregards the background. The tools can therefore quickly detect differences in pixel intensity that are likely to be an abnormal change in a given picture and alert to a possible security breach.\u201d<\/p>\n

Promising results<\/h4>\n

\u201cWe are delighted with the results our model is producing so far,\u201d says Dr Sanchez. \u201cIt can be used across a wide range of uses including classification, activity recognition, object recognition, video surveillance, monitoring and video anomaly detection, and it is suitable for use in real-time situations. The biggest advance, however, has been successfully reducing the demand on training time to hours, computational power, storage and memory. It means the tool could now run on something like a mobile phone or a CCTV camera itself \u2013 no longer needing a powerful computer.\u201d<\/p>\n

The team\u2019s findings show huge promise for the security industry.<\/p>\n

Dr Sanchez continues: \u201cThere are a number of big advantages for a company wanting to employ this kind of solution. 24-hour surveillance is a demanding job that will still need a human eye, but using an automatic real-time monitoring system in the background would give added back-up.<\/p>\n

\u201cIn addition, a single operator may have the responsibility of watching many screens, streaming many views simultaneously, but the human eye cannot pay attention to every single camera and so a real-time monitoring solution would help to do the job more efficiently. Plus, the low computation power requirement of the tool would allow it to be run on a mobile phone, making it portable and freeing up security personnel to move around a given area to make physical checks.\u201d<\/p>\n

Dr Victor Sanchez<\/p>\n

Researcher from the Computer Science department at the University of Warwick.<\/p>\n

This invention is now the subject of a patent application PCT GB2018\/058103, and the researchers are working with Warwick Ventures to explore licensing opportunities for this new solution.<\/p>\n

For more information visit: https:\/\/warwick.ac.uk\/siplab\/research\/<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

Keeping it Real-time : advances in video analytics for CCTV This year, it is…<\/p>\n","protected":false},"author":19,"featured_media":7547,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"om_disable_all_campaigns":false,"footnotes":""},"categories":[90,2,39],"tags":[],"class_list":["post-7574","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-analytics","category-editors-choice","category-security-technology"],"acf":[],"yoast_head":"\nAdvances in video analytics for CCTV - City Security Magazine<\/title>\n<meta name=\"description\" content=\"The dramatic growth in the use of video is driving the demand for more efficient ways of analysing video data, particularly for CCTVs.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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