This paper presents a spatiotemporal saliency visual attention model based on maximum entropy. A dynamic saliency map is created by calculating entropies in every corresponding local region between the current and some previous frames in a short video. In the same time, four low-level visual features including color contrast, intensity contrast, orientation and texture, are extracted and are co...

The majority of visual attention models is based on the concept of saliency map, a two-dimensional map that encodes the saliency of objects in the surrounding world. We attempt a short review of current implementations and present our first thoughts on extending the classical saliency-based model by using motion and prior knowledge.

In this paper, we propose a new framework to predict visual scanpaths of observers while they freely watch a visual scene. The visual fixations are inferred from bottom-up saliency and several oculomotor biases. Bottom-up saliency is represented by a saliency map whereas the oculomotor biases (saccade amplitudes and saccade orientations) are modeled using public eye tracking datasets. Our exper...

This paper introduces a model of gaze behavior suitable for robotic active vision. Built upon a saliency map taking into account motion saliency, the presented model estimates the dynamics of different eye movements, allowing to switch from fixational movements, to saccades and to smooth pursuit. We investigate the effect of the embodiment of attentive visual selection in a pan-tilt camera syst...

Two recent papers (Foulsham, Barton, Kingstone, Dewhurst, & Underwood, 2009; Mannan, Kennard, & Husain, 2009) report that neuropsychological patients with a profound object recognition problem (visual agnosic subjects) show differences from healthy observers in the way their eye movements are controlled when looking at images. The interpretation of these papers is that eye movements can be mode...

Most models of visual search, whether involving overt eye movements or covert shifts of attention, are based on the concept of a saliency map, that is, an explicit two-dimensional map that encodes the saliency or conspicuity of objects in the visual environment. Competition among neurons in this map gives rise to a single winning location that corresponds to the next attended target. Inhibiting...

We propose an online visual tracking algorithm by learning discriminative saliency map using Convolutional Neural Network (CNN). Given a CNN pre-trained on a large-scale image repository in offline, our algorithm takes outputs from hidden layers of the network as feature descriptors since they show excellent representation performance in various general visual recognition problems. The features...

The spatio-temporal visual system is a computational approach to model the bottom-up visual saliency for HDR input by combining spatial and temporal visual features. The main advantage of this system is that it will reduce the cognitive processing efforts. Computational models of visual attention can be applied to areas such as computer graphics, video coding and quality assessment. The propose...

Finding the salient regions in videos has been a very active topic. In this work we compare the modelisation of visual attention on egocentric video recordings for two different points of view. We are interested in finding the relation between the visual saliency maps of the viewer of visual content and the actors (person executing the actions). This question is of importance because the buildi...