Vision Science and Technology at NASA: Results of a Workshop

A broad review is given of vision science and technology within NASA. The subject is defined and its applications in both NASA and the nation at large are noted. A survey of current NASA efforts is given, noting strengths and weaknesses of the NASA program

Automatic segmentation and reconstruction of traffic accident scenarios from mobile laser scanning data

Virtual reconstruction of historic sites, planning of restorations and attachments of new building parts, as well as forest inventory are few examples of fields that benefit from the application of 3D surveying data. Originally using 2D photo based documentation and manual distance measurements, the 3D information obtained from multi camera and laser scanning systems realizes a noticeable improvement regarding the surveying times and the amount of generated 3D information. The 3D data allows a detailed post processing and better visualization of all relevant spatial information. Yet, for the extraction of the required information from the raw scan data and for the generation of useable visual output, time-consuming, complex user-based data processing is still required, using the commercially available 3D software tools. In this context, the automatic object recognition from 3D point cloud and depth data has been discussed in many different works. The developed tools and methods however, usually only focus on a certain kind of object or the detection of learned invariant surface shapes. Although the resulting methods are applicable for certain practices of data segmentation, they are not necessarily suitable for arbitrary tasks due to the varying requirements of the different fields of research. This thesis presents a more widespread solution for automatic scene reconstruction from 3D point clouds, targeting street scenarios, specifically for the task of traffic accident scene analysis and documentation. The data, obtained by sampling the scene using a mobile scanning system is evaluated, segmented, and finally used to generate detailed 3D information of the scanned environment. To realize this aim, this work adapts and validates various existing approaches on laser scan segmentation regarding the application on accident relevant scene information, including road surfaces and markings, vehicles, walls, trees and other salient objects. The approaches are therefore evaluated regarding their suitability and limitations for the given tasks, as well as for possibilities concerning the combined application together with other procedures. The obtained knowledge is used for the development of new algorithms and procedures to allow a satisfying segmentation and reconstruction of the scene, corresponding to the available sampling densities and precisions. Besides the segmentation of the point cloud data, this thesis presents different visualization and reconstruction methods to achieve a wider range of possible applications of the developed system for data export and utilization in different third party software tools

Network-based system for acoustic mapping of urban areas

The paper presents both a general idea and basic assumptions of the research project, which was started a year ago at Technical University of Silesia, Poland and primarily has been focused on the Region of Upper Silesia. At present, the project is prepared to cover other regions of the country. In particular, the research area of this project contains the problems of preparing and utilizing the acoustical maps of towns that ought to be prepared in accordance with the EC directive com468 (2000). The main two assumptions of the project are as follows: 1) the maps will be prepared by means of advanced computer-based tools of the GIS and GPS classes, 2) both the procedures of developing and utilizing the acoustical maps will be executed in the form of group-work using the PIONIER (Polish Optical Internet) NREN and Intranet tools for online collaboration and audiovisual communication with utilization of resources available at network and HPC centers across the country. It is assumed that the system as primarily being developed for the needs of local scale mapping thanks to the network approach will be adaptable also for larger (regional) scale enterprises. The paper discusses briefly the current state of research in the mentioned field in Poland. The second part of the paper presents the timetable of further activities with a specification of expected results. Apart from the 'technical' problems of acoustic mapping of urban areas, the paper also deals with some 'non-technical' aspects of this field of activity. The final part of the paper introduces some perspectives of dissemination of results of the reported research in the process of European enlargement.

A collective intelligence approach for building student's trustworthiness profile in online learning

(c) 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Information and communication technologies have been widely adopted in most of educational institutions to support e-Learning through different learning methodologies such as computer supported collaborative learning, which has become one of the most influencing learning paradigms. In this context, e-Learning stakeholders, are increasingly demanding new requirements, among them, information security is considered as a critical factor involved in on-line collaborative processes. Information security determines the accurate development of learning activities, especially when a group of students carries out on-line assessment, which conducts to grades or certificates, in these cases, IS is an essential issue that has to be considered. To date, even most advances security technological solutions have drawbacks that impede the development of overall security e-Learning frameworks. For this reason, this paper suggests enhancing technological security models with functional approaches, namely, we propose a functional security model based on trustworthiness and collective intelligence. Both of these topics are closely related to on-line collaborative learning and on-line assessment models. Therefore, the main goal of this paper is to discover how security can be enhanced with trustworthiness in an on-line collaborative learning scenario through the study of the collective intelligence processes that occur on on-line assessment activities. To this end, a peer-to-peer public student's profile model, based on trustworthiness is proposed, and the main collective intelligence processes involved in the collaborative on-line assessments activities, are presented.Peer ReviewedPostprint (author's final draft

Automatic Multiple Choice Examination Questions Marking and Grade Generator Software

This paper discusses a feasible software solution that enables automatic marking andgrading of scripts. Technology keeps expanding, and more advanced innovations arebeing implemented with time. The marking and allocation of grades for examina-tion scripts through human efforts are gradually becoming a thing of the past. Hence,machines and software applications are introduced to make the entire marking andgrading of examination scripts more efficient, fast, and less tedious. Computer visionis an artificial intelligence (AI) knowledge domain that ensures devices obtain usefulinformation from digital images, videos, and other visual inputs. Image processingand recognition, a unique part of computer vision alongside the python program-ming language and the OpenCV library was employed for this project. These are themost used in developing most recent applications that utilize, to some extent, arti-ficial intelligence to attain specific desired results. The result of the project seeksto develop a maintainable android software application that uses image processingtechnology to scan patterns or images and grades results of multiple-choice questionscripts based on a set marking scheme. This ensures that desired results are obtainedwhile increasing efficiency and productivity

Efficient Benchmarking of Algorithm Configuration Procedures via Model-Based Surrogates

The optimization of algorithm (hyper-)parameters is crucial for achieving peak performance across a wide range of domains, ranging from deep neural networks to solvers for hard combinatorial problems. The resulting algorithm configuration (AC) problem has attracted much attention from the machine learning community. However, the proper evaluation of new AC procedures is hindered by two key hurdles. First, AC benchmarks are hard to set up. Second and even more significantly, they are computationally expensive: a single run of an AC procedure involves many costly runs of the target algorithm whose performance is to be optimized in a given AC benchmark scenario. One common workaround is to optimize cheap-to-evaluate artificial benchmark functions (e.g., Branin) instead of actual algorithms; however, these have different properties than realistic AC problems. Here, we propose an alternative benchmarking approach that is similarly cheap to evaluate but much closer to the original AC problem: replacing expensive benchmarks by surrogate benchmarks constructed from AC benchmarks. These surrogate benchmarks approximate the response surface corresponding to true target algorithm performance using a regression model, and the original and surrogate benchmark share the same (hyper-)parameter space. In our experiments, we construct and evaluate surrogate benchmarks for hyperparameter optimization as well as for AC problems that involve performance optimization of solvers for hard combinatorial problems, drawing training data from the runs of existing AC procedures. We show that our surrogate benchmarks capture overall important characteristics of the AC scenarios, such as high- and low-performing regions, from which they were derived, while being much easier to use and orders of magnitude cheaper to evaluate