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In this paper, we present a novel framework for representation of images as a combination of multiple mid-level feature descriptor representation based group of visual words. The mid-level feature representation is computed on discriminative patches of the image to build a lexicon, the visual words of which are used to represent the shape within that image. The proposed image representation method...
We here study the problem of visual attention computation in video of driving environment via the learning from eye movements. We collect a large-scale database of eye movements from 28 subjects on 30 videos of road scenes, which simulate the driving environment. The analysis on this eye movement database reveals that visual attention in driving environment is directed by high-level cognitive factors...
This paper addresses the problem of discovering activities and their temporal significance in surveillance videos in an unsupervised manner. We propose a generative model that can jointly capture the activities and their behaviour over time. We use multinomial distribution over local motion features to model activities and a mixture distribution over their time stamps to capture the multi-modal temporal...
This paper presents the results of an experimental study on designing for self-efficacy in a game based driving simulator. Self-efficacy refers to how peoplepsilas beliefs in their capabilities affect their actions. The results show that the design of the feedback system can be used to increase self-efficacy measures thus affecting performance in a driving simulator environment. Self-efficacy has...
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