Background Filtering for Improving of Object Detection in Images
Vrusias, BL, Qin, G and Gillam, L (2010) Background Filtering for Improving of Object Detection in Images In: 20th IEEE International Conference on Pattern Recognition (ICPR), 2010-08-23 - 2010-08-27, Istanbul, Turkey.
Available under License : See the attached licence file.
We propose a method for improving object recognition in street scene images by identifying and filtering out background aspects. We analyse the semantic relationships between foreground and background objects and use the information obtained to remove areas of the image that are misclassified as foreground objects. We show that such background filtering improves the performance of four traditional object recognition methods by over 40%. Our method is independent of the recognition algorithms used for individual objects, and can be extended to generic object recognition in other environments by adapting other object models
|Item Type:||Conference or Workshop Item (Paper)|
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|Divisions:||Faculty of Engineering and Physical Sciences > Computing Science|
|Deposited By:||Symplectic Elements|
|Deposited On:||06 Nov 2012 16:55|
|Last Modified:||16 Feb 2013 16:45|
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