View Direction, Surface Orientation and Texture Orientation for Perception of Surface Shape

Textures are commonly used to enhance the representation of shape in non-photorealistic rendering applications such as medical drawings. Textures that have elongated linear elements appear to be superior to random textures in that they can, by the way they conform to the surface, reveal the surface shape. We observe that shape following hache marks commonly used in cartography and copper-plate illustration are locally similar to the effect of the lines that can be generated by the intersection of a set of parallel planes with a surface. We use this as a basis for investigating the relationships between view direction, texture orientation and surface orientation in affording surface shape perception. We report two experiments using parallel plane textures. The results show that textures constructed from planes more nearly orthogonal to the line of sight tend to be better at revealing surface shape. Also, viewing surfaces from an oblique view is much better for revealing surface shape than viewing them from directly above

Change blindness: eradication of gestalt strategies

Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task

A Novel Framework for Highlight Reflectance Transformation Imaging

We propose a novel pipeline and related software tools for processing the multi-light image collections (MLICs) acquired in different application contexts to obtain shape and appearance information of captured surfaces, as well as to derive compact relightable representations of them. Our pipeline extends the popular Highlight Reflectance Transformation Imaging (H-RTI) framework, which is widely used in the Cultural Heritage domain. We support, in particular, perspective camera modeling, per-pixel interpolated light direction estimation, as well as light normalization correcting vignetting and uneven non-directional illumination. Furthermore, we propose two novel easy-to-use software tools to simplify all processing steps. The tools, in addition to support easy processing and encoding of pixel data, implement a variety of visualizations, as well as multiple reflectance-model-fitting options. Experimental tests on synthetic and real-world MLICs demonstrate the usefulness of the novel algorithmic framework and the potential benefits of the proposed tools for end-user applications.Terms: "European Union (EU)" & "Horizon 2020" / Action: H2020-EU.3.6.3. - Reflective societies - cultural heritage and European identity / Acronym: Scan4Reco / Grant number: 665091DSURF project (PRIN 2015) funded by the Italian Ministry of University and ResearchSardinian Regional Authorities under projects VIGEC and Vis&VideoLa

Neural Mechanisms Underlying the Perception of Three-Dimensional Shape from Texture: Adaptation and Aftereffects

Input into the visual system is two-dimensional (2D) and yet we effortlessly perceive the world around us as three-dimensional (3D). How we are able to accurately extract 3D shape information from the 2D representations that fall on the retina remains largely unknown. Although much research has been conducted that investigates higher levels of form processing (i.e. face recognition), less is known about the mechanisms that underlie the perception of simple 3D shape. Previous studies in our lab have shown that our ability to perceive 3D shape from texture cues relies on the visibility of orientation flows -- patterns that run parallel to the surface curvature of a 3D shape. Using the psychophysical technique of selective adaptation, we have further characterized the neural mechanisms that underlie the accurate perception of 3D shape. In Experiment One, we examined whether orientation flows that are defined by second order contours convey 3D shape, whether they induce 3D shape aftereffects, and whether these aftereffects are invariant to the patterns that define the orientation flows. Aftereffects were obtained and 3D shape was conveyed using stimuli in which orientation flows were defined by two classes of second order contours, and adapting to second order stimuli caused 3D shape aftereffects in first order stimuli. These results can be explained by the adaptation of 3D shape-selective neurons in extrastriate regions that invariantly extract first- and second order orientation flows from striate and extrastriate signals. In Experiment Two, we were interested in determining to what extent these neural mechanisms are invariant to differences in spatial frequency. We chose adapting/test stimuli that differed in spatial frequency by a factor of three, consistent with documented frequency bandwidths of V1 and V2 neurons. Shape aftereffects were obtained, indicating that these neural mechanisms are invariant to differences in spatial frequency by a factor of 3. Furthermore, these neural mechanisms are invariant to the patterns in which spatial frequency was varied (i.e., stimuli in which the orientation flows were created by first- or second order properties). Both of these properties are indicative of neurons that are located in extrastriate cortex. In Experiment Three, we were interested in testing to what extent these neural mechanisms were selective for retinal position by misaligning adapting and test stimuli by 2°, which corresponded to a single convexity or concavity in our corrugated surfaces. Our results suggest that 3D shape-selective mechanisms that respond to luminance modulated orientation flows appear to be sensitive to shifts in position of 2°. Overall, our results indicate that there are 3D shape mechanisms that are pattern invariant, invariant to differences in spatial frequencies by a factor of 3, and that exhibit position selectivity to shifts in retinal position of 2°. Taken together, these results implicate 3D shape mechanisms that are located in extrastriate cortex

About the nature of Kansei information

Kansei studies refer to the more and more holistic consideration of the cognitive and affective processes which occur during user experience. In addition, few studies deal with the experience of the designers during the design process, and its influence on the final design outputs. Historically kansei engineering has been firstly focused on the semantic differential approach. Afterwards emotions were integrated into kansei approaches. The semantic differential approach enabled to evaluate products and then to generate automatically design solutions with semantic input data. Thereafter, evaluations have been completed by physiological measurements in order to reduce the subjectivity involved in those evaluations and also to capture some unconscious reactions. This implementation is still in process. Today kansei studies have been much enriched from the three disciplines of design science, psychology and artificial intelligence. The cross influence between these disciplines brought new dimensions into kansei approaches (multisensory design information, personality, values, and culture, new formalisms and algorithms) which lead progressively towards the consideration of a whole enriched kansei experience. We propose in this paper a description of the nature of kansei information. Then we present some major orientations for kansei evaluation. Finally we propose an overall table gathering information about kansei dimensions and formats.AN

Imagining circles: empirical data and a perceptual model for the arc-size illusion

An essential part of visual object recognition is the evaluation of the curvature of both an object's outline as well as the contours on its surface. We studied a striking illusion of visual curvature--the arc-size illusion (ASI)--to gain insight into the visual coding of curvature. In the ASI, short arcs are perceived as flatter (less curved) compared to longer arcs of the same radius. We investigated if and how the ASI depends on (i) the physical size of the stimulus and (ii) on the length of the arc. Our results show that perceived curvature monotonically increases with arc length up to an arc angle of about 60°, thereafter remaining constant and equal to the perceived curvature of a full circle. We investigated if the misjudgment of curvature in the ASI translates into predictable biases for three other perceptual tasks: (i) judging the position of the centre of circular arcs; (ii) judging if two circular arcs fall on the circumference of the same (invisible) circle and (iii) interpolating the position of a point on the circumference of a circle defined by two circular arcs. We found that the biases in all the above tasks were reliably predicted by the same bias mediating the ASI. We present a simple model, based on the central angle subtended by an arc, that captures the data for all tasks. Importantly, we argue that the ASI and related biases are a consequence of the fact that an object's curvature is perceived as constant with viewing distance, in other words is perceptually scale invariant

Motion sequence analysis in the presence of figural cues

Published in final edited form as: Neurocomputing. 2015 January 5, 147: 485–491The perception of 3-D structure in dynamic sequences is believed to be subserved primarily through the use of motion cues. However, real-world sequences contain many figural shape cues besides the dynamic ones. We hypothesize that if figural cues are perceptually significant during sequence analysis, then inconsistencies in these cues over time would lead to percepts of non-rigidity in sequences showing physically rigid objects in motion. We develop an experimental paradigm to test this hypothesis and present results with two patients with impairments in motion perception due to focal neurological damage, as well as two control subjects. Consistent with our hypothesis, the data suggest that figural cues strongly influence the perception of structure in motion sequences, even to the extent of inducing non-rigid percepts in sequences where motion information alone would yield rigid structures. Beyond helping to probe the issue of shape perception, our experimental paradigm might also serve as a possible perceptual assessment tool in a clinical setting.The authors wish to thank all observers who participated in the experiments reported here. This research and the preparation of this manuscript was supported by the National Institutes of Health RO1 NS064100 grant to LMV. (RO1 NS064100 - National Institutes of Health)Accepted manuscrip

A perceptual-statistics shading model

The process of surface perception is complex and based on several influencing factors, e.g., shading, silhouettes, occluding contours, and top down cognition. The accuracy of surface perception can be measured and the influencing factors can be modified in order to decrease the error in perception. This paper presents a novel concept of how a perceptual evaluation of a visualization technique can contribute to its redesign with the aim of improving the match between the distal and the proximal stimulus. During analysis of data from previous perceptual studies, we observed that the slant of 3D surfaces visualized on 2D screens is systematically underestimated. The visible trends in the error allowed us to create a statistical model of the perceived surface slant. Based on this statistical model we obtained from user experiments, we derived a new shading model that uses adjusted surface normals and aims to reduce the error in slant perception. The result is a shape-enhancement of visualization which is driven by an experimentally-founded statistical model. To assess the efficiency of the statistical shading model, we repeated the evaluation experiment and confirmed that the error in perception was decreased. Results of both user experiments are publicly-available datasets