Sallama Athab - Parallel Priority Region Approach to Detect Background

Sallama Athab joined the School of Science and Technology University of Northampton as a PhD research visitor from University of Babylon on a six-moth visit. The purpose of her visit is to develop her PhD research further whilst at Northampton. 

Up-coming paper:

 Sallama Athab ,Hala Bahja, Yinghui Zhang (2013) 
"Parallel Priority Region Approach to Detect Background" 
Oral Presentation 
ICCCISE 2013: International Conference on Computer, Communication and Information Sciences and Engineering. 
Paris, France, 7-8 October 2013

Abstract
Background detection is essential in video analyses; optimization is often needed to achieve the real time calculation. Information gathered by dual cameras placed in the front and rear part of Autonomous Vehicle (AV) are integrated for background detection. In this paper, real time calculation is achieved on the proposed technique by using Priority Regions (PR) and Parallel Processing together where each frame is divided into regions then each region process in parallel. PR division depends upon driver view limitation. Background detection system built on the Temporal Difference (TD) and Gaussian Filtering (GF). Temporal Difference and Gaussian Filtering with multi threshold and sigma(weight) value are be based on PR characterize. Experiment result is prepared on real scene. Comparison of the speed and accuracy with traditional background detection techniques, effectiveness of PR and parallel processing are discussed in this paper as well.

Related
Sallama Athab - Filter to Detect Objects in Video from Moving Platform

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Sallama Athab - Detect Objects from a moving platform

 Sallama Athab joined the School of Science and Technology University of Northampton as a PhD research visitor from University of Babylon on a six-moth visit. The purpose of her visit is to develop her PhD research further whilst at Northampton. 

Recent paper:

Moving Area Filter to Detect Object in Video Sequence from Moving Platform

Sallama Athab ,Hala Bahjat

International Conference on Computer, Communication and Information Sciences and Engineering. 5-6 September 2013.

Abstract
Detecting object in video sequence is a challenging mission for identifying, tracking moving objects. Background removal considered as a basic step in detected moving objects tasks. Dual static cameras placed in front and rear moving platform gathered information which is used to detect objects. Background change regarding with speed and direction moving platform, so moving objects distinguished become complicated. In this paper, we propose framework allows detection moving object with variety of speed and direction dynamically. Object detection technique built on two levels the first level apply background removal and edge detection to generate moving areas. The second level apply Moving Areas Filter (MAF) then calculate Correlation Score (CS) for adjusted moving area. Merging moving areas with closer CS and marked as moving object. Experiment result is prepared on real scene acquired by dual static cameras without overlap in sense. Results showing accuracy in detecting objects compared with optical flow and Mixture Module Gaussian (MMG), Accurate ratio produced to measure accurate detection moving object.


Future paper:

1 Sallama Athab ,Hala Bahja, Yinghui Zhang (2013) "Parallel Priority Region Approach to Detect Background" Oral Presentation ICCCISE 2013: International Conference on Computer, Communication and Information Sciences and Engineering. Paris, France, 7-8 October 2013