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Image indexing is one of the most difficult challenges facing the computer vision community. Addressing this issue, we designed an innovative approach to obtain an accurate label for images by taking into account the social aspects of human-based computation. The proposed approach is highly discriminative in comparison to an ordinary content-based image(More)
We introduce an interactive framework for image understanding, a game that is enjoyable and provide valuable image annotations. When people play the game, they provide useful information about contents of an image. In reality the most accurate method to describe the content of an image is manual labelling. Our approach is to motivate people to label imagers(More)
This project is mainly focused to develop system for animal researchers & wild life photographers to overcome so many challenges in their day life today. When they engage in such situation, they need to be patiently waiting for long hours, maybe several days in whatever location and under severe weather conditions until capturing what they are interested(More)
Face recognition under varying illumination and dimensionality reduction has been a key problem in the field of Computer Vision. An extension of Principal Component Analysis (PCA) called Independent Component Analysis (ICA) has been utilised in this paper as a feature extraction technique. In the proposed approach three feature selection techniques have(More)
In this paper, an interactive approach to obtain semantic annotations for images is presented. The proposed approach aims at what millions of single, online and cooperative gamers are keen to do, enjoy themselves in a competitive environment. It focuses on computer gaming and the use of humans in a widely distributed fashion. This approach deviates from the(More)
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