SMARTENC

Smart Video Encoders for Wireless Surveillance Networks

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 Obiettivo del progetto (Objective)

'Video surveillance systems became one of the most essential tools people rely on for keeping buildings, businesses, urban areas, and borders secure. As the number of deployed cameras increase rapidly, the ability of human observers to analyze the video in real-time is becoming almost impossible. Video analytics engines embedded in networked cameras and video analytics servers provide tools for automatically analyzing the scenes. However, the video compression hardware used in cameras is decoupled from and not aware of the embedded analytics engines, servers and other cameras possibly capturing the same scene. The objective of the proposed project is to design smart embedded video encoders that maximize the content and reliability of information extracted by the video analytics while minimizing the cost of deployment. Video compression algorithms that utilize the video analysis metadata to improve the prediction efficiency, computational resource and rate budget allocation will be designed. Objective video quality metrics specifically tailored for surveillance applications will be implemented to improve and judge the proposed techniques. Application specific quality measurement will be a new concept since previous studies in the literature focused on determining the perceptual distortion in images and videos. We also propose collaborative design of the video encoders located at cameras capturing overlapping scenes. Video analytics metadata will be utilized for joint multi-camera rate control and prediction algorithms. Finally, the project will tackle the robust data transmission challenges of the wireless surveillance systems. Wireless ad-hoc network state measurement and adaptive video streaming rate control techniques will be developed. A novel and scalable surveillance system will be devised upon the successful completion of the project.'

Introduzione (Teaser)

Video compression is not optimised for automated analysis. An EU team is developing new methods for encoding compression plus algorithms for video streaming, leading to improved automatic video analysis.

Descrizione progetto (Article)

A group of technical issues affect the efficiency of video surveillance cameras. Typically, the compression system will be separate from other analytical elements such as face recognition, and optimised for human viewing rather than machine analysis.

The EU funded the single-member 'Smart video encoders for wireless surveillance networks' (SMARTENC) project to rectify the situation. Over four years to June 2015, the team will design video encoders to work with analytical systems in surveillance cameras. The aim is to improve both performance of video analysis and compression quality. Work will involve the development of new encoding techniques and streaming algorithms.

Work during the first half of the project focused on creating new software for video handling and processing, called Object Oriented Video Processing Architecture (OVA). The results were incorporated into two other EU projects (ITEA2 and SPY).

As components of OVA, the project designed and developed four algorithms for real-time video analysis. The innovations allow detection and tracking of moving objects, video stabilisation and generation of panoramic video. An additional algorithm, developed in collaboration with a commercial organisation, improves efficiency of real-time video encoding. The project also devised a camera system optimised for testing the software.

The work to date has resulted in several patent applications being filed, as well as conference publications.

SMARTENC has developed novel systems that address the inefficiencies of conventional video compression. As a result, automated video processing for surveillance will also be more efficient, potentially leading to greater public safety.