ISLAMABAD: Information Technology and Telecommunications Ministry is in the process of developing an automatic surveillance system for video streams which would provide great support to law enforcement agencies (LEAs) in combating terrorism and capturing culprits.
The peaceful purposes of this project are monitoring crowd, restricted access points and counting the occurrence of specific persons.
From a technological perspective, one tested technology that can provide some protection against terrorism is video surveillance.
They are quite common these days, resulting in a sharp rise in surveillance data during last a few years. This rate of increase has been gathering speed in underdeveloped and developed countries alike. Only in the United Kingdom, there are 4.2 million closed circuit TV cameras installed, one per every 14 people.
National ICT Fund, a department of the ministry is funding the project at a cost of Rs 26.62 million. The principal investigator’s organisation (PIO) is Al-Khwarizmi Institute of Computer Science, University of Engineering and Technology, Lahore, and the project is expected to be completed by August next year.
As per details of the project on Thursday, technically, this project mainly encompasses an automatic understanding of visual scenes based on individual contents/high-level features (HLFs) present in the videos.
By extracting high-level features, such as faces age, gender, emotions, actions and objects, human-human interaction, human-object interaction, scene settings etc., we can easily obtain the interpretation of a video stream.
The video surveillance procedure is becoming common in Pakistan as well. A huge amount of data is collected by cameras every day, but question remains how to make meaningful use of this data. It seems futile to store the whole day data, especially if it was a serene day, or even if some suspicious activity was observed in some part of the day.
The storage mechanism should be intelligent enough to log only the most relevant coverage of the video stream. Even then the problem remains of storing huge amount of data which is expensive with respect to storage media required.
This project addresses this problem by using image processing methods for automatic understanding of video streams while keeping a check on storage needs of streaming data.
The system will use surveillance cameras installed in security sensitive areas which will capture and store videos of daily life activities happening around in that area. Automatic understanding of these videos will be performed using image processing methods which can result in the development of several useful applications.
In addition, textual description of the video sequence will be generated using natural language processing which will save huge storage requirement.
A web based utility for videos searching and summarization will be provided to search most relevant videos in accordance with the security needs.
The project provides substitutes for human monitoring of surveillance cameras. Such human monitoring can be compromised with drowsiness or over work scenarios; therefore, an automated solution is highly desirable since it would run all days and nights and on virtually any number of cameras without human intervention.
Currently, image processing community is focused on identification of individual objects, their properties and events in a video stream. This project extends this work to the next level. It is a step ahead of keyword based tagging as it captures relations between key-words associated with videos, thus clarifying the context between them.
Initially, HLFs are identified from a video sequence. Secondly, these HLFs are combined together using natural language processing techniques to generate smooth descriptions of a videos sequence. Finally, this automatically generated language description is summarized to present most important contents in the provided video sequence.
Successful implementation of this project can lead to useful applications related to video searching, retrieval, mining and warehousing.
Given a textual description or a keyword, user of the system can search a video. In this way, user can save time while retrieving only desired events instead of watching whole video.
In addition, proposed research work open new horizons for statistical explanation of the video sequences. These statistics will be helpful in taking precautionary measures for eradicating terrorism activities. Finally, a web based searching and summarization tool will be generated for the end users of this research work.
