Consistent Viewing and Interaction for Multiple Users in Projection-Based VR Systems

In projection-based Virtual Reality (VR) systems, typically only one headtracked user views stereo images rendered from the correct view position. For other users, who are presented a distorted image, moving with the first user's head motion, it is difficult to correctly view and interact with 3D objects in the virtual environment. In close-range VR systems, such as the Virtual Workbench, distortion effects are especially large because objects are within close range and users are relatively far apart. On these systems, multi-user collaboration proves to be difficult. In this paper, we analyze the problem and describe a novel, easy to implement method to prevent and reduce image distortion and its negative effects on close-range interaction task performance. First, our method combines a shared camera model and view distortion compensation. It minimizes the overall distortion for each user, while important user-personal objects such as interaction cursors, rays and controls remain distortion-free. Second, our method retains co-location for interaction techniques to make interaction more consistent. We performed a user experiment on our Virtual Workbench to analyze user performance under distorted view conditions with and without the use of our method. Our findings demonstrate the negative impact of view distortion on task performance and the positive effect our method introduces. This indicates that our method can enhance the multi-user collaboration experience on close-range, projection-based VR systems.     

Registration of challenging image pairs: initialization, estimation, and decision

Our goal is an automated 2D-image-pair registration algorithm capable of aligning images taken of a wide variety of natural and man-made scenes as well as many medical images. The algorithm should handle low overlap, substantial orientation and scale differences, large illumination variations, and physical changes in the scene. An important component of this is the ability to automatically reject pairs that have no overlap or have too many differences to be aligned well.We propose a complete algorithm, including techniques for initialization, for estimating transformation parameters, and for automatically deciding if an estimate is correct. Keypoints extracted and matched between images are used to generate initial similarity transform estimates, each accurate over a small region. These initial estimates are rank-ordered and tested individually in succession. Each estimate is refined using the Dual-Bootstrap ICP algorithm, driven by matching of multiscale features. A three-part decision criteria, combining measurements of alignment accuracy, stability in the estimate, and consistency in the constraints, determines whether the refined transformation estimate is accepted as correct. Experimental results on a data set of 22 challenging image pairs show that the algorithm effectively aligns 19 of the 22 pairs and rejects 99.8% of the misalignments that occur when all possible pairs are tried. The algorithm substantially out-performs algorithms based on keypoint matching alone.     

Battery State-Of-Charge Based Altitude Controller for Small, Low Cost Multirotor Unmanned Aerial Vehicles

Small unmanned aerial vehicles (UAV) are typically driven by Lithium polymer batteries. The batteries have their own dynamics, which changes during discharge. Classical approaches to altitude control assume a time-invariant system and therefore fail. Adaptive controllers require an identified system model which is often unavailable. Battery dynamics can be characterized and used for a battery model-based controller. This controller is useful in situations when no feedback from actuators (such as RPM or thrust) is available. After measuring the battery dynamics for two distinct types of batteries, a controller is designed and experimentally verified, showing a consistent performance during entire discharge test and a consequent flight verification.     

Computing occluding and transparent motions

Computing the motions of several moving objects in image sequences involves simultaneous motion analysis and segmentation. This task can become complicated when image motion changes significantly between frames, as with camera vibrations. Such vibrations make tracking in longer sequences harder, as temporal motion constancy cannot be assumed. The problem becomes even more difficult in the case of transparent motions.A method is presented for detecting and tracking occluding and transparent moving objects, which uses temporal integration without assuming motion constancy. Each new frame in the sequence is compared to a dynamic internal representation image of the tracked object. The internal representation image is constructed by temporally integrating frames after registration based on the motion computation. The temporal integration maintains sharpness of the tracked object, while blurring objects that have other motions. Comparing new frames to the internal representation image causes the motion analysis algorithm to continue tracking the same object in subsequent frames, and to improve the segmentation.     

An application of a decision–theoretic model to a quota-free selection problem.

Demonstrated a possible application of a threshold utility model for evaluating the student selection procedure based on 1,554 applications made to the Faculty of Humanities at the Hebrew University of Jerusalem. Results show that the predictor was useful, unless its costs were very large. This conclusion is generalizable across the different definitions of success, since the utility ratios and the prior probabilities of success tended to neutralize one another. (14 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Generating heavy particles with energy and momentum conservation

We propose a novel algorithm, called REGGAE, for the generation of momenta of a given sample of particle masses, evenly distributed in Lorentz-invariant phase space and obeying energy and momentum conservation. In comparison to other existing algorithms, REGGAE is designed for the use in multiparticle production in hadronic and nuclear collisions where many hadrons are produced and a large part of the available energy is stored in the form of their masses. The algorithm uses a loop simulating multiple collisions which lead to production of configurations with reasonably large weights.

Program summary

Program title: REGGAE (REscattering-after-Genbod GenerAtor of Events)Catalogue identifier: AEJR_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEJR_v1_0.htmlProgram obtainable from: CPC Program Library, Queen?s University, Belfast, N. IrelandLicensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.htmlNo. of lines in distributed program, including test data, etc.: 1523No. of bytes in distributed program, including test data, etc.: 9608Distribution format: tar.gzProgramming language: C++Computer: PC Pentium 4, though no particular tuning for this machine was performed.Operating system: Originally designed on Linux PC with g++, but it has been compiled and ran successfully on OS X with g++ and MS Windows with Microsoft Visual C++ 2008 Express Edition, as well.RAM: This depends on the number of particles which are generated. For 10 particles like in the attached example it requires about 120 kB.Classification: 11.2Nature of problem: The task is to generate momenta of a sample of particles with given masses which obey energy and momentum conservation. Generated samples should be evenly distributed in the available Lorentz-invariant phase space.Solution method: In general, the algorithm works in two steps. First, all momenta are generated with the GENBOD algorithm. There, particle production is modeled as a sequence of two-body decays of heavy resonances. After all momenta are generated this way, they are reshuffled. Each particle undergoes a collision with some other partner such that in the pair center of mass system the new directions of momenta are distributed isotropically. After each particle collides only a few times, the momenta are distributed evenly across the whole available phase space. Starting with GENBOD is not essential for the procedure but it improves the performance.Running time: This depends on the number of particles and number of events one wants to generate. On a LINUX PC with 2 GHz processor, generation of 1000 events with 10 particles each takes about 3 s.     

Colour and rotation invariant textural features based on Markov random fields

A visual appearance of natural materials significantly depends on acquisition circumstances, particularly illumination conditions and viewpoint position, whose variations cause difficulties in the analysis of real scenes. We address this issue with novel texture features, based on fast estimates of Markovian statistics, that are simultaneously rotation and illumination invariant. The proposed features are invariant to in-plane material rotation and illumination spectrum (colour invariance), they are robust to local intensity changes (cast shadows) and illumination direction. No knowledge of illumination conditions is required and recognition is possible from a single training image per material. The material recognition is tested on the currently most realistic visual representation - Bidirectional Texture Function (BTF), using CUReT and ALOT texture datasets with more than 250 natural materials. Our proposed features significantly outperform leading alternatives including Local Binary Patterns (LBP, LBP-HF) and texton MR8 methods.     

Developing and evaluating language courseware

The paper sets out twenty proposals for the development and evaluation of Computer Assisted Language Learning (CALL) programs. These proposals emerge from special characteristics of language instruction and of the use of computers to assist in language instruction. We combine theoretically-based assumptions with empirical findings drawn from investigation of language courseware for Hebrew speakers in Israel. We first list four unique features of language instruction: (1) the object-language-meta-language distinction; (2) computer as written medium vs. language as primary spoken medium; (3) teaching of second language skills vs. linguistics; (4) the computer as an electronic tool vs. the computer as a cognitive entity simulating the speaker. We then show how these unique characteristics of language instruction (mother-tongue and foreign language) impose special proposals on language courseware. These proposals should be observed in the development of language courseware and in the evaluation of such programs. Clearly, these proposals integrate with general courseware proposals. Michal Ephratt (Ph.D., computational linguistics) completed post-doctoral studies at the University of Rochester. She has been on the staff of the Dept. of Hebrew Linguistics, University of Haifa, since 1988. Some of her publications include Root-Pattern Array: The Main Tool of Hebrew Word Formation (Hebrew University, 1985); and What's in a Joke? in Advances in Artificial Intelligence, Natural Language and Knowledge-based Systems (Springer-Verlag, 1990).This paper is based on work the author did as a consultant in the National Courseware Evaluation Department of the Ministry of Education. I wish to thank Esther Diamant, head of the department, for making the study possible.     

Evolution of efficient real-time non-linear image filters for FPGAs

Image processing represents a research field in which high-quality solutions have been obtained using various soft computing techniques. Evolutionary algorithms constitute a class of stochastic search methods that are applicable in both optimization and design tasks. In the area of circuit design Cartesian Genetic Programming has often been utilized in combination with an algorithm of Evolutionary Strategy. Digital image filters represent a specific class of circuits whose design can be performed by means of this approach. Switching filters are advanced non-linear filtering techniques in which the main idea is to detect and filter the noise pixels while keeping the uncorrupted pixels unchanged in order to increase the quality of the resulting image. The aim of this article is to present a robust design technique based on Cartesian Genetic Programming for the automatic synthesis of switching image filters intended for real-time processing applications. The robustness of the proposed evolutionary approach is evaluated using four design problems including the removal of salt and pepper noise, random shot noise, impulse burst noise and impulse burst noise combined with random shot noise. An extensive evaluation is performed in order to compare the properties of the evolved switching filters with the best conventional solutions. The evaluation has shown that the evolved switching filters exhibit a very good trade off between the quality of filtering and the implementation cost in field programmable gate arrays.