Representation Of Real Objects Research Articles

Representations of real objects and pictures in the dorsal and ventral visual streams differ based on physical stimulus distance

Representations of real objects and pictures in the dorsal and ventral visual streams differ based on physical stimulus distance

On the Validity of Virtual Reality Applications for Professional Use: A Case Study on Color Vision Research and Diagnosis

In recent years, there have been very important advances in graphic computing and technology related to the capture and representation of real objects in both 2 and 3 dimensions. One of these technologies is virtual reality, which can be incorporated into common tasks in research laboratories, especially in laboratories related to color vision and lighting research. To incorporate virtual reality devices into research tasks, newly developed applications must be validated with existing and known tests or techniques. The objective of this work was to study the validity of a commercial VR system for research and diagnosis in color vision. We carried out a comparative study on the behavior of these immersive systems for viewing 3D scenes in real time using a color vision test. In particular, we implemented a virtual version of the Farnsworth-Munsell 100 Hue test and compared the results obtained by 17 normal and 3 defective observers in both the physical and virtual tests. The results show that the functionality of both tests is very similar and that the diagnosis of both methods is equivalent. Detailed analysis of the results of both tests indicates that there is a slight difference in scale between the two tests. This difference in scale indicates a greater difficulty in the case of the virtual test but does not affect the final diagnosis. This could be due to the greater difficulty in using a head-mounted display (HMD).

Similarities and differences in the representation of real objects, 2-D images, and 3-D augmented reality displays: Insights from inverse multidimensional scaling

Similarities and differences in the representation of real objects, 2-D images, and 3-D augmented reality displays: Insights from inverse multidimensional scaling

Similarities and differences in the representation of real objects versus 2-D planar images and 3-D augmented reality displays: insights from inverse multidimensional scaling

Similarities and differences in the representation of real objects versus 2-D planar images and 3-D augmented reality displays: insights from inverse multidimensional scaling

Similarities and differences in the representation of real objects and images: insights from inverse multidimensional scaling

Two-dimensional (2-D) images of objects are commonly used as proxies to access the organization of conceptual knowledge in the brain. However, various studies from our lab highlight differences between images and real objects at the neural level (Snow et al, 2011), as well as in their contribution to memory (Snow et al., 2014), attention (Gomez et al., in press), and decision-making (Romero et al., in press). Asking an observer to judge the similarities among a set of objects can provide unique insights into the underlying neural representations in human cortex (Mur et al, 2013). Here, we used inverse multidimensional scaling (Kriegeskorte and Mur 2012) to investigate the properties that observers use to characterize objects displayed as 2-D images versus real objects. Observers arranged 21 different items so that the distances between them reflect their perceived dissimilarities. Half of the participants (n=68) arranged 2-D images on a computer monitor; the other half arranged the corresponding real-world exemplars manually on a table top. Critically, participants were not given a criterion to sort the objects, but were free to use any dimension they liked to group the items. By correlating models based on the various sorting criteria with the dissimilarity matrix obtained by the behavioral ratings, we identified the properties that observers used to separate the items within each format. Stepwise linear regression showed that both common and different criteria were used to arrange images and real objects. For example, for both formats, the location where the item is typically encountered was a salient dimension, as was elongation. However, unlike 2-D images, real objects were also sorted based on properties relevant for their manipulation, specifically, their physical size and weight. These results suggest that despite their similarly with respect to the semantic properties, 2-D images lack the representational richness of their real-world counterparts.

Multimodal Sensing Interface for Haptic Interaction

This paper investigates the integration of a multimodal sensing system for exploring limits of vibrato tactile haptic feedback when interacting with 3D representation of real objects. In this study, the spatial locations of the objects are mapped to the work volume of the user using a Kinect sensor. The position of the user’s hand is obtained using the marker-based visual processing. The depth information is used to build a vibrotactile map on a haptic glove enhanced with vibration motors. The users can perceive the location and dimension of remote objects by moving their hand inside a scanning region. A marker detection camera provides the location and orientation of the user’s hand (glove) to map the corresponding tactile message. A preliminary study was conducted to explore how different users can perceive such haptic experiences. Factors such as total number of objects detected, object separation resolution, and dimension-based and shape-based discrimination were evaluated. The preliminary results showed that the localization and counting of objects can be attained with a high degree of success. The users were able to classify groups of objects of different dimensions based on the perceived haptic feedback.

Application of Low-cost Tracking Systems in Educational Training Applications

Abstract The paper presents problems related to measurement accuracy of tracking systems, which are widely used in immersive simulations based on Virtual Reality technology. Possibility of tracking movements of the user makes the simulation in virtual environment more realistic. This is very important in case of training simulations of situations, where mistake of an operator would threaten the life and health of himself or other people or could lead to substantial material losses. The authors’ many years of experience in creating interactive Virtual Reality applications allows them to conclude, that possibility of use of professional tracking systems is often not possible for educational facilities like schools or universities due to budget reasons. Professional tracking systems are usually more accurate and have more programming support of their use in Virtual Reality applications than the low-cost solutions. However, low-cost devices are often tens of times cheaper than the professional systems. The research presented in the paper is an attempt of answering the question – how the immersion level related to accuracy of position and orientation representation of real object in a virtual environment influences the evaluation of usefulness of a given tracking system for training applications. A particular attention was paid to tracking of user's movement, which allows him to naturally interact with the computer generated environment. Displaying a simulation reacting properly and smoothly to real movements performed by the user will allow him to develop the most necessary reflexes, which would not be possible using only non-natural interaction devices, such as mouse or keyboard. On the other hand, development of improper reflexes related to user's position being wrongly read can bring more harm than benefit to the training process. The paper presents results of study of accuracy of one of the tracking systems available on the market – the PST 55 system. This device uses retro-active markers, which are widely used also in measurement systems not dedicated to use in the VR system. The real position of tracked objects was verified using an industrial photogrammetric measurement system TRITOP from GOM company. The results of the comparative study allowed to determine how accurate is the studied tracking system and how the accuracy affects the feeling of immersion.

The influence of noise on the generalized dimensions

Abstract Digital images of real objects are often interpreted as fractals and computer algorithms enable the determination of fractal dimensions, such as the generalized correlation dimensions. But digital images are restricted representations of the real object and an exact determination or calculation is not possible. Digital images have a limited spatial resolution and they are always contaminated with noise that may disturb the representation of the real object. The influence of noise on the calculated values of the generalized correlation dimensions has been investigated in this study. A practical fractal, a digital image of a cancer spheroid, as well as three mathematically defined fractals, the Sierpinski triangle, a fern and a modified Menger gasket were used and the results were compared. Noise with well defined levels was added to noise free images. Three distinct noise distributions were applied and the results were compared. It turned out, that noise partially has a high and distinct influence on the generalized dimensions but the influence is very similar for each one of the fractals. Because of this similarity, the results are reliable and the representation of real objects by digital images is reliable, too.

Imagining Real and Unreal Things: Evidence of a Dissociation in Autism

Current theories of visual imagery hold that the same neural processes govern both the representation of real objects and the representation of imagined (but real) objects. Here we test whether the representation of imagined (real) objects and the representation of imagined (but unreal) objects depend on the same or different neurocognitive processes. A likely clinical group for a dissociation between these two types of imagination are children with autism, since they show deficits in imaginative play, impoverished imagination is part of their diagnosis, but they can search for hidden objects. The present study explored imagination in autism using experimental methods. Experiment 1 investigated if children with autism could introduce changes to their representations of people and houses, using Karmiloff-Smith's (1989) technique of asking children to draw "impossible" people or houses. Results showed that children with autism were significantly worse than matched controls in their ability to introduce "unreal" changes to their representations of people and houses. Instead, they tended to draw real people or objects. Experiment 2 investigated whether the performance in Experiment 1 by children with autism was due to an inability to disengage from "real world" representations, as executive dysfunction theorists would argue. To do this, the experimenter instructed them on what to draw and how to draw it. Results showed that even when executive control passed to the experimenter in this way, the children with autism were still significantly impaired in their ability to draw imaginary but unreal things relative to the matched controls. Experiment 3 investigated whether the results from Experiments 1 and 2 arose because of a generativity deficit in autism, which might be the executive dysfunction theorists' alternative account. To test this, the same subjects were given a test of Verbal Fluency and a test of imagining multiple functions of a brick. Results showed that the children with autism were no worse than clinical controls in their ability to generate ideas about real objects, suggesting that a global generativity deficit cannot explain the previous findings. Rather, these results point to a specific impairment in the ability to imagine unreal objects. This is discussed in terms of its possible neural dissociability from other kinds of imagery, and in terms of its possible relationship to theory of mind.

Strategies for Solving Collision-free Trajectories Problems for Mobile and Manipulator Robots

This article addresses issues involved in programming auto matic solvers for collision-avoidance problems in robotics. It presents a refined notion of empty space and shows that solution methods to the find-path problem all reduce to graph-search techniques. The article introduces an intrinsic tree structure for empty space that reduces the complexity of the problem and discusses inherent limitations to implemen tations, taking into account approximation and computer geometry problems. Computational complexity and practical limitations of the methods are addressed. This study shows how to develop a very simple and efficient solution to prob lems of gross motion for general manipulator robots. The approach is compatible with arbitrary assumptions about ob stacle geometry and representation of real objects in a com puter.