Selecting input and output devices to be used in virtual walkthroughs is an important issue as it may have significant impact in usability and comfort. This paper presents a user study meant to compare the usability of two input devices used for walkthroughs in a virtual environment with a Head-Mounted Display. User performance, satisfaction, ease of use and comfort, were compared with two different input devices: a two button mouse and a joystick from a gamepad. Participants also used a desktop to perform the same tasks in order to assess if the participant groups had similar profiles. The results obtained by 45 participants suggest that both input devices have a comparable usability in the used conditions and show that participants generally performed better with the desktop; a discussion of possible causes is presented.
In medical image processing and analysis it is often required to perform segmentation for quantitative measures
of extent, volume and shape.
The validation of new segmentation methods and tools usually implies comparing their various outputs among
themselves (or with a ground truth), using similarity metrics. Several such metrics are proposed in the literature
but it is important to select those which are relevant for a particular task as opposed to using all metrics and
therefore avoiding additional computational cost and redundancy.
A methodology is proposed which enables the assessment of how different similarity and discrepancy metrics
behave for a particular comparison and the selection of those which provide relevant data.
The complexity of a polygonal mesh is usually reduced by applying a simplification method, resulting in a similar
mesh having less vertices and faces. Although several such methods have been developed, only a few observer
studies are reported comparing the perceived quality of the simplified meshes, and it is not yet clear how the
choice of a given method, and the level of simplification achieved, influence the quality of the resulting mesh, as
perceived by the final users. Similar issues occur regarding other mesh processing methods such as smoothing.
Mesh quality indices are the obvious less costly alternative to user studies, but it is also not clear how they relate
to perceived quality, and which indices best describe the users behavior.
This paper describes on going work concerning the evaluation of perceived quality of polygonal meshes using
observer studies, while looking for a quality index which estimates user performance. In particular, given some
results obtained in previous studies, a new experimental protocol was designed and a study involving 55 users
was carried out, which allowed their validation, as well as further insight regarding mesh quality, as perceived
by human observers.
Virtual and Augmented Reality are developing rapidly: there is a multitude of environments and experiments in several
laboratories using from simple HMD (Head-Mounted Display) visualization to more complex and expensive 6-wall
projection CAVEs, and other systems. Still, there is not yet a clear emerging technology in this area, nor commercial
applications based on such a technology are used in large scale. In addition to the fact that this is a relatively recent
technology, there is little work to validate the utility and usability of Virtual and Augmented Reality environments when
compared with the traditional desktop set-up. However, usability evaluation is crucial in order to design better systems
that respond to the users' needs, as well as for identifying applications that might really gain from the use of such
technologies.
This paper presents a preliminary usability evaluation of a low-cost Virtual and Augmented Reality environment under
development at the University of Aveiro, Portugal. The objective is to assess the difference between a traditional desktop
set-up and a Virtual/Augmented Reality system based on a stereo HMD. Two different studies were performed: the first
one was qualitative and some feedback was obtained from domain experts who used an Augmented Reality set-up as well
as a desktop in different data visualization scenarios. The second study consisted in a controlled experiment meant to
compare users' performances in a gaming scenario in a Virtual Reality environment and a desktop. The overall
conclusion is that these technologies still have to overcome some hardware problems. However, for short periods of time
and specific applications, Virtual and Augmented Reality seems to be a valid alternative since HMD interaction is
intuitive and natural.
KEYWORDS: Lung, Data modeling, Neodymium, Visual process modeling, Visualization, Data analysis, 3D modeling, Statistical modeling, Statistical analysis, Error analysis
The complexity of a polygonal mesh model is usually reduced by applying a simplification method, resulting in
a similar mesh having less vertices and faces. Although several such methods have been developed, only a few
observer studies are reported comparing them regarding the perceived quality of the obtained simplified meshes,
and it is not yet clear how the choice of a given method, and the level of simplification achieved, influence the
quality of the resulting model, as perceived by the final users. Mesh quality indices are the obvious less costly
alternative to user studies, but it is also not clear how they relate to perceived quality, and which indices best
describe the users behavior.
Following on earlier work carried out by the authors, but only for mesh models of the lungs, a comparison
among the results of three simplification methods was performed through (1) quality indices and (2) a controlled
experiment involving 65 observers, for a set of five reference mesh models of different kinds. These were simplified
using two methods provided by the OpenMesh library - one using error quadrics, the other additionally using
a normal flipping criterion - and also by the widely used QSlim method, for two simplification levels: 50% and
20% of the original number of faces. The main goal was to ascertain whether the findings previously obtained
for lung models, through quality indices and a study with 32 observers, could be generalized to other types of
models and confirmed for a larger number of observers. Data obtained using the quality indices and the results
of the controlled experiment were compared and do confirm that some quality indices (e.g., geometric distance
and normal deviation, as well as a new proposed weighted index) can be used, in specific circumstances, as
reasonable estimators of the user perceived quality of mesh models.
Meshes are currently used to model objects, namely human organs and other structures. However, if they have a large number of triangles, their rendering times may not be adequate to allow interactive visualization, a mostly desirable feature in some diagnosis (or, more generally, decision) scenarios, where the choice of adequate views is important. In this case, a possible solution consists in showing a simplified version while the user interactively chooses the viewpoint and, then, a fully detailed version of the model to support its analysis. To tackle this problem, simplification methods can be used to generate less complex versions of meshes. While several simplification methods have been developed and reported in the literature, only a few studies compare them concerning the perceived quality of the obtained simplified meshes.
This work describes an experiment conducted with human observers in order to compare three different simplification methods used to simplify mesh models of the lungs. We intended to study if any of these methods allows a better-perceived quality for the same simplification rate.
A protocol was developed in order to measure these aspects. The results presented were obtained from 32 human observers. The comparison between the three mesh simplification methods was first performed through an Exploratory Data Analysis and the significance of this comparison was then established using other statistical methods. Moreover, the influence on the observers' performances of some other factors was also investigated.
Quantitative evaluation of the performance of segmentation algorithms on medical images is crucial before their clinical use can be considered. We have quantitatively compared the contours obtained by a pulmonary segmentation algorithm to contours manually-drawn by six expert imaiologists on the same set of images, since the ground truth is unknown. Two types of variability (inter-observer and intra-observer) should be taken into account in the performance evaluation of segmentation algorithms and several methods to do it have been proposed. This paper describes the quantitative evaluation of the performance of our segmentation algorithm using several figures of merit, exploratory and multivariate data analysis and non parametric tests, based on the assessment of the inter-observer variability of six expert imagiologists from three different hospitals and the intra-observer variability of two expert imagiologists from the same hospital. As an overall result of this comparison we were able to claim that the consistency and accuracy of our pulmonary segmentation algorithm is adequate for most of the quantitative requirements mentioned by the imagiologists. We also believe that the methodology used to evaluate the performance of our algorithm is general enough to be applicable to many other segmentation problems on medical images.
MultiProtocol Label Switching (MPLS) technology allows the support of multiple services with different Quality of Service (QoS) requirements in classical IP networks. In an MPLS domain, packet flows belonging to a particular class are classified in the same Forward Equivalence Class (FEC). Based on different FECs, each service can be set up in the network through logical networks. Each logical network is a set of Label Switched Paths (LSPs), one for each service traffic trunk. The network-dimensioning problem is formulated as the determination of routes for all LSPs to achieve the least cost physical network. To solve this problem some widely known heuristics are used and two enhancement algorithms are proposed that allow for significant gains when compared with the basic heuristics. The heuristics tested include a genetic algorithm, a greedy based heuristic and a lagrangean relaxation based heuristic. The enhancements are proposed for application to the greedy based heuristic and to the lagrangean heuristic. The results show that the enhanced lagrangean heuristic is the best overall technique for the case studies presented. This technique yields significant average gains when compared to the basic lagrangean heuristic.
The visual analysis of Stereoelectroencephalographic (SEEG) signals in their anatomical context is aimed at the understanding of the spatio-temporal dynamics of epileptic processes. The magnitude of these signals may be encoded by graphical glyphs, having a direct impact on the perception of the values. Our study is devoted to the evaluation of the quantitative visualization of these signals, specifically to the influence of the coding scheme of the glyphs on the understanding and the analysis of the signals. This work describes an experiment conducted with human observers in order to evaluate three different coding schemes used to visualize the magnitude of SEEG signals in their 3D anatomical context. We intended to study if any of these coding schemes allows better performances for the human observers in two aspects: accuracy and speed. A protocol has been developed in order to measure these aspects. The results that will be presented in this work were obtained from 40 human observers. The comparison between the three coding schemes has first been performed through an Exploratory Data Analysis (EDA). The statistical significance of this comparison has then been established using nonparametric methods. The influence on the observers' performance of some other factors has also been investigated.
Segmentation of thoracic X-Ray Computed Tomography images is a mandatory pre-processing step in many automated or semi- automated analysis tasks such us region identification, densitometric analysis, or even for 3D visualization purposes when a stack of slices has to be prepared for surface or volume rendering. In this work, we present a fully automated and fast method for pulmonary contour extraction and region identification. Our method combines adaptive intensity discrimination, geometrical feature estimation and morphological processing resulting into a fast and flexible algorithm. A complementary but not less important objective of this work consisted on a quality assessment study of the developed contour detection technique. The automatically extracted contours were statistically compared to manually drawn pulmonary outlines provided by two radiologists. Exploratory data analysis and non-parametric statistical tests were performed on the results obtained using several figures of merit. Results indicate that, besides a strong consistence among all the quality indexes, there is a wider inter-observer variability concerning both radiologists than the variability of our algorithm when compared to each one of the radiologists. As an overall conclusion we claim that the consistence and accuracy of our detection method is more than acceptable for most of the quantitative requirements mentioned by the radiologists.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.