Volume 32 #3

Contents

1. Fundamental principles of odor perception for higher fatty aids V. Ì. Ganshina and E. P. Zinkevich
2. Attractors for visual attention and visual scene analysis
3. Influence of the pre-exposure of visual objects on the discrimination of sounds in children with a delay in mental and language development
4. Neural network-based feature point descriptors for registration of optical and SAR images
5. Artificial training data generation for the task of character recognition of fields of russian passport
6. Methods of training data augmentation in the task of image classification
7. Neural network model of multisensory detector vehicle presence in the classification zone of charging points
8. Learning a metric feature space with siamese networks for disparity map computation
9. A method of object recognition based on formal properties specification applied to locating objects in aerial photographs

We proposed a method for the description of attention shift in early vision. The results obtained show that there are some specific features which attract strong visual attention – “visual attractors”. The strongest attractors were water reflection and fragments of distorted and strange objects (for example – the objects on S. Daly’s pictures). We have also found that the subjects of “visual type” have more wide attention field and understand the 3D structure of the scene immediately. In contrast, the subjects of “analytic type” catch the features in a restricted area and cannot understand the 3D structure of a scene. We suggest that the first points of fixation are determined by the interaction between complicated neuron ensembles which are formed in visual experience and which work in early vision as parallel processors (“top-down” model).

Key words: preattentive vision, scan-path, visual attractors, visual attention, image scanning trajectories, visual models, functional brain asymmetry

DOI: 10.1134/S0235009218030083

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