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.

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:
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