Lili Tcheang

A psychophysically calibrated controller for navigating through large environments in a limited free-walking space

Experience indicates that the sense of presence in a virtual environment is enhanced when the participants are able to actively move through it. When exploring a virtual world by walking, the size of the model is usually limited by the size of the available tracking space. A promising way to overcome these limitations are motion compression techniques, which decouple the position in the real and virtual world by introducing imperceptible visual-proprioceptive conflicts. Such techniques usually precalculate the redirection factors, greatly reducing their robustness. We propose a novel way to determine the instantaneous rotational gains using a controller based on an optimization problem. We present a psychophysical study that measures the sensitivity of visual-proprioceptive conflicts during walking and use this to calibrate a real-time controller. We show the validity of our approach by allowing users to walk through virtual environments vastly larger than the tracking space.

SET: a pupil detection method using sinusoidal approximation

Mobile eye-tracking in external environments remains challenging, despite recent advances in eye-tracking software and hardware engineering. Many current methods fail to deal with the vast range of outdoor lighting conditions and the speed at which these can change. This confines experiments to artificial environments where conditions must be tightly controlled. Additionally, the emergence of low-cost eye tracking devices calls for the development of analysis tools that enable non-technical researchers to process the output of their images. We have developed a fast and accurate method (known as “SET”) that is suitable even for natural environments with uncontrolled, dynamic and even extreme lighting conditions. We compared the performance of SET with that of two open-source alternatives by processing two collections of eye images: images of natural outdoor scenes with extreme lighting variations (“Natural”); and images of less challenging indoor scenes (“CASIA-Iris-Thousand”). We show that SET excelled in outdoor conditions and was faster, without significant loss of accuracy, indoors. SET offers a low cost eye-tracking solution, delivering high performance even in challenging outdoor environments. It is offered through an open-source MATLAB toolkit as well as a dynamic-link library (“DLL”), which can be imported into many programming languages including C# and Visual Basic in Windows OS (www.eyegoeyetracker.co.uk).

A Novel Feature Combination Methods for Saliency-Based Visual Attention

In the field of visual attention, bottom-up or saliency-based visual attention allows primates to detect non-specific conspicuous objects or targets in cluttered scenes. Simple multi-scale “feature maps” detect local spatial discontinuities in intensity, color, orientation, and are combined into a “saliency” map. In this paper, we propose a Saliency Map based on feature weighted, in which the Rough Sets is used to assign the weighting for every feature. This method measures the contribution of each conspicuity map obtained from the feature maps to saliency map. And it also carries out a dynamic weighting of individual conspicuity maps. We obtain results, which enrich the theory of Saliency detection. We use the real data of natural scenes to demonstrate the effectiveness of the algorithm.

Posterior parietal cortex and visuospatial control in near and far space

Neuropsychological studies of patients with visuospatial neglect have shown differences in perceptual deficits for information in near space (i.e. near to the body) and information in far space. It has been suggested that among the many areas of the human brain, a number of areas are associated with a set of spatial maps specialized for visuospatial control related to this spatial distinction. This paper reviews how parietal cortex is thought to be involved in visuospatial neglect in relation to its control of visuospatial attention in the left and right visual fields and at different viewing distances. In particular, the importance of regions of the parietal cortex in the pathogenesis of neglect and in spatial attention and perception is discussed. Parietal cortex may control different distributions of attention across space by allocating specific attentional resources in near and far space while also showing attentional asymmetry across visual fields. Transcranial magnetic stimulation (TMS) as a technique offers the advantage of examining the direct behavioral effect of disruption of many of these areas with excellent temporal and spatial resolution. We discuss the use of TMS and the insights it may offer regarding the roles of these areas in neglect as well as normal visuospatial perception.

Culture and Math

Cultural differences have been shown across a number of different cognitive domains from vision, language, and music. Mathematical cognition is another domain that is an integral part of modern society and because there are a fixed number of ways in which many math operations can be performed, it is also an apposite tool for cultural comparisons. This discussion examines the literature on mathematical processing in accordance with culture, summarizing the brain regions involved across various mathematical tasks. In doing so, we provide a clear picture of the anatomical similarities and differences between cultures when performing different math tasks. This information is useful to explore the possibility of enhancement of mathematical skills, where different strategies may be applicable in accordance with culture. It also contributes to the evolutionary development of different math skills and the growing theory that anatomical and behavioral studies must account for the cultural identity of their sample.

Saliency based on cortex-like mechanisms

A visual attention system should preferentially locate the most informative spots in complex environments. Feature-integration theory of attention plays an important role in bottom-up computational model for visual attention. This point extremely decreases the detection accuracy and also impacts the performance of the automatic visual attention model. To improve the accuracy of saliency detection in human visual attention, we propose a model based on cortex-like mechanisms. Saliency Criteria are obtained from two pathways: Shannons entropy and sparse representation. And our model not only substantiates the bottom-up model proposed by Itti and HMAX model by Paggio, but also enriches the theory of saliency detection. We demonstrate that the proposed model achieves superior accuracy in comparison to the classical approach in static saliency map generation on real data of natural scenes and psychology stimuli patterns.