Peter J. Passmore

Shape from Shading. I: Surface Curvature and Orientation

The human visual system makes effective use of shading alone in recovering the shape of objects. Pictures of sculptures are readily interpreted—a situation where shading provides virtually the sole cue to shape. However, shading has been considered a poor cue to depth in comparison with retinal disparity and kinetic cues. Curvature discrimination thresholds were measured with the use of a surface-alignment task for a range of surface curvatures from 0.16 cm−1 to 1.06 cm−1. Weber fractions were around 0.1, demonstrating considerable precision in this task. Weber fractions did not vary substantially as a function of surface curvature. Rotation of the light source around the line of sight had no effect on curvature discrimination but rotation towards the viewer increased discrimination thresholds. In contrast, slant discrimination declined with rotation of the light-source vector towards the viewpoint. When a band-limited random grey-level texture was mapped onto the sphere, curvature discrimination thresholds increased gradually as a function of texture contrast, even though texture and shading provided consistent cues to depth. Adding texture also increased slant discrimination thresholds, demonstrating that texture can act as a source of noise in shape-from-shading tasks. The psychophysical findings have been used to evaluate whether current algorithms for shape from shading in computer vision could serve as models of human three-dimensional shape analysis and to highlight low-level intramodular interactions between depth cues. It is demonstrated that, in the case of surfaces defined by shading, curvature descriptions are primary and do not depend upon the prior encoding of surface orientation, and Koenderinks local-shape index is suggested as an alternative intermediate representation of surface shape in the human visual system.

A User Study on Curved Edges in Graph Visualization

Recently there has been increasing research interest in displaying graphs with curved edges to produce more readable visualizations. While there are several automatic techniques, little has been done to evaluate their effectiveness empirically. In this paper we present two experiments studying the impact of edge curvature on graph readability. The goal is to understand the advantages and disadvantages of using curved edges for common graph tasks compared to straight line segments, which are the conventional choice for showing edges in node-link diagrams. We included several edge variations: straight edges, edges with different curvature levels, and mixed straight and curved edges. During the experiments, participants were asked to complete network tasks including determination of connectivity, shortest path, node degree, and common neighbors. We also asked the participants to provide subjective ratings of the aesthetics of different edge types. The results show significant performance differences between the straight and curved edges and clear distinctions between variations of curved edges.

Independent encoding of surface orientation and surface curvature

Marr [(1982) Vision, San Francisco, Calif.: Freeman] proposed that we represent surface geometry in terms of a viewer-centred description of surface orientation and distance. This description is computed by a range of independent processing systems which take as input particular kinds of information present in images, like surface texture, shading, retinal disparity and motion parallax. The outputs of these modules are integrated in order to provide a unitary representation of the layout of visible surfaces. Higher order properties of surface geometry, like surface curvature, might be computed from this symbolic representation or might be encoded independently from the visual information available at the retinae. We measured surface slant and surface curvature discrimination thresholds for surface patches defined by shading, texture and retinal disparity as a function of the elevation of the illumination. We found that observers judgements about the curvature of local surface patches were too precise to be based on a symbolic representation of surface orientation and we conclude that surface curvature is computed directly from depth cues present in the retinal images.

Colour vision model-based approach for segmentation of traffic signs

This paper presents a new approach to segment traffic signs from the rest of a scene via CIECAM, a colour appearance model. This approach not only takes CIECAM into practical application for the first time since it was standardised in 1998, but also introduces a new way of segmenting traffic signs in order to improve the accuracy of colour-based approach. Comparison with the other CIE spaces, including CIELUV and CIELAB, and RGB colour space is also carried out. The results show that CIECAM performs better than the other three spaces with 94%, 90%, and 85% accurate rates for sunny, cloudy, and rainy days, respectively. The results also confirm that CIECAM does predict the colour appearance similar to average observers.

A review of cell assemblies

Since the cell assembly (CA) was hypothesised, it has gained substantial support and is believed to be the neural basis of psychological concepts. A CA is a relatively small set of connected neurons, that through neural firing can sustain activation without stimulus from outside the CA, and is formed by learning. Extensive evidence from multiple single unit recording and other techniques provides support for the existence of CAs that have these properties, and that their neurons also spike with some degree of synchrony. Since the evidence is so broad and deep, the review concludes that CAs are all but certain. A model of CAs is introduced that is informal, but is broad enough to include, e.g. synfire chains, without including, e.g. holographic reduced representation. CAs are found in most cortical areas and in some sub-cortical areas, they are involved in psychological tasks including categorisation, short-term memory and long-term memory, and are central to other tasks including working memory. There is currently insufficient evidence to conclude that CAs are the neural basis of all concepts. A range of models have been used to simulate CA behaviour including associative memory and more process- oriented tasks such as natural language parsing. Questions involving CAs, e.g. memory persistence, CAs’ complex interactions with brain waves and learning, remain unanswered. CA research involves a wide range of disciplines including biology and psychology, and this paper reviews literature directly related to the CA, providing a basis of discussion for this interdisciplinary community on this important topic. Hopefully, this discussion will lead to more formal and accurate models of CAs that are better linked to neuropsychological data.

Effects of viewing and orientation on path following in a medical teleoperation environment

The use of virtual and augmented reality techniques in medicine is rapidly increasing particularly in the area of minimal access surgery. Such surgery is a form of teleoperation in which accurate perception of depth and orientation, navigation, and interaction with the operative space are vital. Virtual and augmented reality techniques will allow us to produce new views of the operative site and introduce extra information into the scene such as safe paths for instruments to follow etc. A path following task is developed and human factors issues are addressed by varying viewing conditions (standard mono, stereo, multiple views and tool-linked view), presence or absence of haptic feedback, and orientation of the task. The results show that performance is improved with haptic feedback, but not by the various viewing conditions and is significantly worse for side aligned orientations.

Effects of viewing condition on user experience of panoramic video

Panoramic video arises at the convergence of TV and virtual reality, and it is necessary to understand how these technologies interact to affect user experience in order to produce useful content. TV and film makers have developed a sophisticated language and set of techniques to achieve directed linear story telling on fixed screens, whereas virtual worlds more often emphasise user led exploration of possibly non-linear narrative and aspects such as presence and immersion in navigable 3D environments. This study focused on the user experience of panoramic video as viewed over two conditions, on a VR headset and using a handheld phone, and compared this to watching on a static screen thus emphasising the differences between traditional and panoramic TV. A qualitative approach to analysis was taken where users participated in semi-structured interviews. A thematic analysis was performed which produced thematic maps describing user experience for each condition. A detailed and nuanced account of emerging themes is given. Subsequently, key themes were identified and graphed to produce user response profiles to the three viewing conditions that highlight differences in user experience in terms of presence, attention, engagement, concentration on story, certainty, comfort and social ease.

User Experience of Panoramic Video in CAVE-like and Head Mounted Display Viewing Conditions

Panoramic 360 video is a rapidly growing part of interactive TV viewing experience due to the increase of both production by consumers and professionals and the availability of consumer headsets used to view it. Recent years have also seen proposals for the development of home systems that could ultimately approximate CAVE-like experiences. The question arises as to the nature of the user experience of viewing panoramic video in head mounted displays compared to CAVE-like systems. User preference seems hard to predict. Accordingly, this study took a qualitative approach to describing user experience of viewing a panoramic video on both platforms, using a thematic analysis. Sixteen users tried both viewing conditions and equal numbers expressed preferences for each display system. The differences in user experience by viewing condition are discussed in detail via themes emerging from the analysis.

Visualization of multidimensional and multimodal tomographic medical imaging data, a case study

Multidimensional tomographic datasets contain physical properties defined over four-dimensional (e.g. spatial–temporal, spatial–spectral), five-dimensional (e.g. spatial–temporal–spectral) or even higher-dimensional domains. Multimodal tomographic datasets contain physical properties obtained with different imaging modalities. In medicine, four-dimensional data are widely used, five-dimensional data are emerging, and multimodal data are being used more often every day. Visualization is vital for medical diagnosis and surgical planning to interpret the information included in imaging data. Visualization of multidimensional and multimodal tomographic imaging data is still a challenging task. As a case study, our work focuses on the visualization of five-dimensional (spatial–temporal–spectral) brain electrical impedance tomography (EIT) data. In this paper, a task-based subset definition scheme is proposed: a task model named Cubic Task Explorer (CTE) is derived to support the visualization task exploration for medical imaging data, and a structured method for visualization system development called Task-based Multi-Dimensional Visualization (TMDV) is proposed. A prototype system named EIT5DVis is developed using the CTE model and TMDV method to visualize five-dimensional brain EIT data.

Models of cell assembly decay

Hebb considered the cell assembly to represent a concept in the brain and thus to be an underlying construct of human thought. He proposed that the cell assembly is a connected group of neurons whose pattern of firing is such that a reverberatory activity persists after the removal of a stimulus. Once a cell assembly is activated something must eventually cause it to decay. Clearly thoughts have to be extinguished to make way for others, the question is how. Various suggestions have been made concerning mechanisms that could cause an assembly to decay in the long term including inhibition by other assemblies and passive fatigue. In this paper two classes of models are used to implement this decay, the first is based on building cell assemblies with specific weights and connections that have a linear decay. The second class is based on manipulating variables within a cell assembly model, creating long term fatigue or activation decay. This class of models may be more biologically plausible than the first, and can produce the expected temporal dynamics in the presence of an ambiguous stimulus. However neither class can yet produce the correct prolongation of activation when the stimulus is re-presented.