A graphical model based solution to the facial feature point tracking problem

In this paper a facial feature point tracker that is motivated by applications such as human-computer interfaces and facial expression analysis systems is proposed. The proposed tracker is based on a graphical model framework. The facial features are tracked through video streams by incorporating statistical relations in time as well as spatial relations between feature points. By exploiting the spatial relationships between feature points, the proposed method provides robustness in real-world conditions such as arbitrary head movements and occlusions. A Gabor feature-based occlusion detector is developed and used to handle occlusions. The performance of the proposed tracker has been evaluated on real video data under various conditions including occluded facial gestures and head movements. It is also compared to two popular methods, one based on Kalman filtering exploiting temporal relations, and the other based on active appearance models (AAM). Improvements provided by the proposed approach are demonstrated through both visual displays and quantitative analysis

Human Motion Trajectory Prediction: A Survey

With growing numbers of intelligent autonomous systems in human environments, the ability of such systems to perceive, understand and anticipate human behavior becomes increasingly important. Specifically, predicting future positions of dynamic agents and planning considering such predictions are key tasks for self-driving vehicles, service robots and advanced surveillance systems. This paper provides a survey of human motion trajectory prediction. We review, analyze and structure a large selection of work from different communities and propose a taxonomy that categorizes existing methods based on the motion modeling approach and level of contextual information used. We provide an overview of the existing datasets and performance metrics. We discuss limitations of the state of the art and outline directions for further research.Comment: Submitted to the International Journal of Robotics Research (IJRR), 37 page

From presence to consciousness through virtual reality

Immersive virtual environments can break the deep, everyday connection between where our senses tell us we are and where we are actually located and whom we are with. The concept of 'presence' refers to the phenomenon of behaving and feeling as if we are in the virtual world created by computer displays. In this article, we argue that presence is worthy of study by neuroscientists, and that it might aid the study of perception and consciousness

Time to start training: A review of cognitive research in sport and proposal for bridging the gap from academia to the field

Research demonstrates the importance of perceptual-cognitive skills, such as pattern matching, anticipation, and decision making in numerous sports, including badminton (Abernethy & Russell, 1987), baseball (Burroughs, 1984), basketball (Allard, Graham, & Paarsalu, 1980), handball (Johnson & Raab, 2003), rugby (Lorains, Ball, & MacMahon, 2013), soccer (Ward & Williams, 2003), squash (Abernethy, 1990), tennis (Haskins, 1965), and volleyball (Borgeaud & Abernethy, 1987). While other factors may be important (e.g., visual search patterns), the accuracy and/or speed with which athletes anticipate their opponent’s intentions and/or decide on an appropriate course of action, as assessed in domain-specific tests designed to simulate and represent real-world sporting demands have been shown to be the best and most reliable predictors of skilled performance in the field (see Mann, Williams, Ward, & Janelle, 2007). Moreover, several studies indicate that when training is based on expert models of superior performance, these skills can be improved and transfer to the field (e.g., Fadde, 2009; Ward, Suss, & Basevitch, 2009). In most elite and everyday sports training contexts, expensive research technology (such as eye-tracking equipment) is not always available to practitioners that would help us better understand the cognitive basis of, and ecological constraints of anticipation and decision-making in a way that could be leveraged to tailor training to improve individual and team performance. However, other technologies are now becoming more readily available to support the development of perceptual-cognitive skills. This is particularly timely, because although there is a growing body of research demonstrating the trainability of perceptual-cognitive skills in sport and their transfer to the field, few researchers have attempted to translate this research into accessible and useful training tools for everyday coaches and athletes (for an example, see Belling, Suss, & Ward, 2014). Moreover, research on the validation of such perceptual-cognitive or decision-making skill training tools is startlingly absent from the literature, not just from research on human factors in sport, but in human factors more broadly. In this research, we review what has worked in the past, what can be leveraged by simple and effective tools for accessible devices (e.g., personal computer, tablet), and how powerful these tools can be by reviewing changes in real world performance following their implementation. An NCAA Division 1 baseball team was given access to Axon Sports Cognitive Training for hitting in baseball for the 2013 season. Batting statistics are compared from the 2012 season, without training present, and 2013 season, with training present. The results suggest that batting improved during the season when cognitive training was available to the players. Implications for future research and application are discussed