AIMC Topic: Pattern Recognition, Visual
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Visual properties and memorising scenes: Effects of image-space sparseness and uniformity.
Attention, perception & psychophysics
Oct 1, 2017
Previous studies have demonstrated that humans have a remarkable capacity to memorise a large number of scenes. The research on memorability has shown that memory performance can be predicted by the content of an image. We explored how remembering an...
Central and peripheral vision for scene recognition: A neurocomputational modeling exploration.
Journal of vision
Apr 1, 2017
What are the roles of central and peripheral vision in human scene recognition? Larson and Loschky (2009) showed that peripheral vision contributes more than central vision in obtaining maximum scene recognition accuracy. However, central vision is m...
Parsing Based on Parselets: A Unified Deformable Mixture Model for Human Parsing.
IEEE transactions on pattern analysis and machine intelligence
Jan 1, 2016
Human parsing, namely partitioning the human body into semantic regions, has drawn much attention recently for its wide applications in human-centric analysis. Previous works often consider solving the problem of human pose estimation as the prerequi...
Human-Machine CRFs for Identifying Bottlenecks in Scene Understanding.
IEEE transactions on pattern analysis and machine intelligence
Jan 1, 2016
Recent trends in image understanding have pushed for scene understanding models that jointly reason about various tasks such as object detection, scene recognition, shape analysis, contextual reasoning, and local appearance based classifiers. In this...
Actions in the Eye: Dynamic Gaze Datasets and Learnt Saliency Models for Visual Recognition.
IEEE transactions on pattern analysis and machine intelligence
Jul 1, 2015
Systems based on bag-of-words models from image features collected at maxima of sparse interest point operators have been used successfully for both computer visual object and action recognition tasks. While the sparse, interest-point based approach ...
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