A visual attention model for dynamic scenes based on motion features

Conference Name:2012 12th International Conference on Control, Automation, Robotics and Vision, ICARCV 2012. Conference Address: Guangzhou, China. Time:December 5, 2012 - December 7, 2012.This paper presents a visual attention model for dynamic scenes based on motion features. The aim is to obtain the region of interest in accordance with the observer's attention in a multiple moving objects situation. Motion speed and motion orientation are selected as the motion features, which make the processing in the model similar to natural observation. A block matching algorithm and a 'center-surround' operation are used to extract features. A motion saliency map is created by the integration of a motion speed conspicuity map and a motion orientation conspicuity map. The experiment shows that the model performs an object-based selection which is effective in complex scenes with efficient background noise suppression. 漏 2012 IEEE

Dynamics of a computational affective model inspired by D枚rner's PSI theory

The PSI theory of Dietrich Dorner touches a number of questions, especially about knowledge representation, perception and bounded rationality. However, since it is formulated within psychology, it has relatively little impact on the discussion of emotion modeling within computer science. This paper introduces a computational model for emotion generation and function by formalizing part of Doner's PSI theory. We also borrowed some technical ideas from MicroPSI, one of the concrete implementations of PSI theory by Joscha Bach. Based on this computational model, a number of simulation experiments have been performed and evaluated. The experimental results show that the emotions of agents controlled by our proposed model can emerge from the interaction between the agents and the environment. Then the dynamics of this computational model are studied using Lewis's dynamic theory of emotions. We successfully found hints of phase transitions in the emotional changes, including trigger, self-amplification and self-stabilization phases, as suggested by Lewis. Based on these simulation results, we argue that this computational model is a quite promising approach of modeling both emotion emergence and dynamics. 漏 2011 Elsevier B.V