Welcome To UTPedia

We would like to introduce you, the new knowledge repository product called UTPedia. The UTP Electronic and Digital Intellectual Asset. It stores digitized version of thesis, dissertation, final year project reports and past year examination questions.

Browse content of UTPedia using Year, Subject, Department and Author and Search for required document using Searching facilities included in UTPedia. UTPedia with full text are accessible for all registered users, whereas only the physical information and metadata can be retrieved by public users. UTPedia collaborating and connecting peoples with university’s intellectual works from anywhere.

Disclaimer - Universiti Teknologi PETRONAS shall not be liable for any loss or damage caused by the usage of any information obtained from this web site.Best viewed using Mozilla Firefox 3 or IE 7 with resolution 1024 x 768.

Video Mining for Observing Human Activities

Altahir Mohammed, Altahir Abdalla Altahir Mohammed (2008) Video Mining for Observing Human Activities. Masters thesis, UNIVERSITI TEKNOLOGI PETRONAS.

[img]
Preview
PDF
Download (80Kb) | Preview
[img]
Preview
PDF
Download (13Kb) | Preview
[img]
Preview
PDF
Download (22Kb) | Preview
[img]
Preview
PDF
Download (215Kb) | Preview
[img]
Preview
PDF
Download (529Kb) | Preview
[img]
Preview
PDF
Download (2735Kb) | Preview
[img]
Preview
PDF
Download (2342Kb) | Preview
[img]
Preview
PDF
Download (858Kb) | Preview
[img]
Preview
PDF
Download (20Kb) | Preview
[img]
Preview
PDF
Download (37Kb) | Preview

Abstract

With the advance in video technology, video cameras have become an integral part of daily life. They are installed in parking lots, traffic intersections, airports, banks, etc. Usually a human operator watches them to catch events of interest in the scene, but this is a tedious and time consuming process requiring constant attention, and leads to inadequate surveillance capability. Therefore, there is an urgent need for automated systems for analysis of surveillance video streams. This thesis presents a novel operational computer vision framework for visual knowledge extraction from human motion. The system captures a video of a scene and classifies those moving objects which are characteristically human. Then perform analyzing and mining operations based on full frame based analysis and inter frame based analysis to interpret the current activity. Moreover, based on selective criteria from full frame board and inter frame board the system evaluate the current activity to assist the security officers to catch the events of interest moreover, creating multi storing scheme for reducing the storage capacity in 24 hours surveillances system.

Item Type: Thesis (Masters)
Subject: UNSPECIFIED
Divisions: Engineering > Electrical and Electronic
Depositing User: Users 5 not found.
Date Deposited: 05 Jun 2012 08:37
Last Modified: 25 Jan 2017 09:44
URI: http://utpedia.utp.edu.my/id/eprint/2892

Actions (login required)

View Item View Item

Document Downloads

More statistics for this item...