A multi-projector CAVE system with commodity hardware and gesture-based interaction

Spatially-immersive systems such as CAVEs provide users with surrounding worlds by projecting 3D models on multiple screens around the viewer. Compared to alternative immersive systems such as HMDs, CAVE systems are a powerful tool for collaborative inspection of virtual environments due to better use of peripheral vision, less sensitivity to tracking errors, and higher communication possibilities among users. Unfortunately, traditional CAVE setups require sophisticated equipment including stereo-ready projectors and tracking systems with high acquisition and maintenance costs. In this paper we present the design and construction of a passive-stereo, four-wall CAVE system based on commodity hardware. Our system works with any mix of a wide range of projector models that can be replaced independently at any time, and achieves high resolution and brightness at a minimum cost. The key ingredients of our CAVE are a self-calibration approach that guarantees continuity across the screen, as well as a gesture-based interaction approach based on a clever combination of skeletal data from multiple Kinect sensors.Preprin

Estimating intrinsic camera parameters from the fundamental matrix using an evolutionary approach

Calibration is the process of computing the intrinsic (internal) camera parameters from a series of images. Normally calibration is done by placing predefined targets in the scene or by having special camera motions, such as rotations. If these two restrictions do not hold, then this calibration process is called autocalibration because it is done automatically, without user intervention. Using autocalibration, it is possible to create 3D reconstructions from a sequence of uncalibrated images without having to rely on a formal camera calibration process. The fundamental matrix describes the epipolar geometry between a pair of images, and it can be calculated directly from 2D image correspondences. We show that autocalibration from a set of fundamental matrices can simply be transformed into a global minimization problem utilizing a cost function. We use a stochastic optimization approach taken from the field of evolutionary computing to solve this problem. A number of experiments are performed on published and standardized data sets that show the effectiveness of the approach. The basic assumption of this method is that the internal (intrinsic) camera parameters remain constant throughout the image sequence, that is, the images are taken from the same camera without varying such quantities as the focal length. We show that for the autocalibration of the focal length and aspect ratio, the evolutionary method achieves results comparable to published methods but is simpler to implement and is efficient enough to handle larger image sequences

An Experimental Hybrid User Interface for Collaboration

We present EMMIE (Environment Management for Multi-user Information Environments), an experimental user interface to a collaborative augmented environment. Users share a 3D virtual space and manipulate virtual objects representing information to be discussed. This approach not only allows for cooperation in a shared physical space, but also addresses tele-collaboration in physically separate but virtually shared spaces. We refer to EMMIE as a hybrid user interface because it combines a variety of different technologies and techniques, including virtual elements such as 3D widgets, and physical objects such as tracked displays and input devices. See-through head-worn displays overlay the virtual environment on the physical environment. Our research prototype includes additional 2D and 3D displays, ranging from palm-sized to wall-sized, allowing the most appropriate one to be used for any task. Objects can be moved among displays (including across dimensionalities) through drag & drop. In analogy to 2D window managers, we describe a prototype implementation of a shared 3Denvironment manager that is distributed across displays, machines, and operating systems. We also discuss two methods we are exploring for handling information privacy in such an environment

Hybrid Focal Stereo Networks for Pattern Analysis in Homogeneous Scenes

In this paper we address the problem of multiple camera calibration in the presence of a homogeneous scene, and without the possibility of employing calibration object based methods. The proposed solution exploits salient features present in a larger field of view, but instead of employing active vision we replace the cameras with stereo rigs featuring a long focal analysis camera, as well as a short focal registration camera. Thus, we are able to propose an accurate solution which does not require intrinsic variation models as in the case of zooming cameras. Moreover, the availability of the two views simultaneously in each rig allows for pose re-estimation between rigs as often as necessary. The algorithm has been successfully validated in an indoor setting, as well as on a difficult scene featuring a highly dense pilgrim crowd in Makkah.Comment: 13 pages, 6 figures, submitted to Machine Vision and Application

Implementation of an Autonomous Impulse Response Measurement System

Data collection is crucial for researchers, as it can provide important insights for describing phenomena. In acoustics, acoustic phenomena are characterized by Room Impulse Responses (RIRs) occurring when sound propagates in a room. Room impulse responses are needed in vast quantities for various reasons, including the prediction of acoustical parameters and the rendering of virtual acoustical spaces. Recently, mobile robots navigating within indoor spaces have become increasingly used to acquire information about its environment. However, little research has attempted to utilize robots for the collection of room acoustic data. This thesis presents an adaptable automated system to measure room impulse responses in multi-room environments, using mobile and stationary measurement platforms. The system, known as Autonomous Impulse Response Measurement System (AIRMS), is divided into two stages: data collection and post-processing. To automate data collection, a mobile robotic platform was developed to perform acoustic measurements within a room. The robot was equipped with spatial microphones, multiple loudspeakers and an indoor localization system, which reported real time location of the robot. Additionally, stationary platforms were installed in specific locations inside and outside the room. The mobile and stationary platforms wirelessly communicated with one another to perform the acoustical tests systematically. Since a major requirement of the system is adaptability, researchers can define the elements of the system according to their needs, including the mounted equipment and the number of platforms. Post-processing included extraction of sine sweeps and the calculation of impulse responses. Extraction of the sine sweeps refers to the process of framing every acoustical test signal from the raw recordings. These signals are then processed to calculate the room impulse responses. The automatically collected information was complemented with manually produced data, which included rendering of a 3D model of the room, a panoramic picture. The performance of the system was tested under two conditions: a single-room and a multiroom setting. Room impulse responses were calculated for each of the test conditions, representing typical characteristics of the signals and showing the effects of proximity from sources and receivers, as well as the presence of boundaries. This prototype produces RIR measurements in a fast and reliable manner. Although some shortcomings were noted in the compact loudspeakers used to produce the sine sweeps and the accuracy of the indoor localization system, the proposed autonomous measurement system yielded reasonable results. Future work could expand the amount of impulse response measurements in order to further refine the artificial intelligence algorithms

Universal Reconfigurable Translator Module (URTM) Final Report

This report describes the Universal Reconfigurable Translation Module, or URTM. The URTM was developed by Sigma Space Corporation for NASA in order to translate specific serial protocols, both logically and physically. At present, the prototype configuration has targeted MIL-STD-1553B (RT and BC), IEEE 1394b (Firewire), and ECSS-E-50-12A (SpaceWire). The objectives of this program were to study the feasibility of a configurable URTM to translate serial link data as might be used in a space-flight mission and to design, develop, document, and deliver an engineering prototype model of the URTM with a path to spaceflight. By simply connecting two of the three Physical Interface Modules (PIM) on either end of the RPTM (Reconfigurable Protocol Translator Module), the URTM then self configures via a library of interface translation functions, thereby allowing the two data links to communicate seamlessly

Seamless Navigation using UWB-based Multisensor System

This work presents an Ultra-wideband-based (UWB) approach to seamless positioning and navigation applied in a real test-bed. It deploys two different solutions for positioning estimation in function of the operational environment. Outdoors, a classical hybridization between Global Navigation Satellite System (GNSS) and Inertial Measurement Unit (IMU) is applied while indoors, an UWB/INS integration is performed relying on a low-cost commercial platform which integrates both UWB unit and IMU. The implementation of this procedure will be presented with more details in the paper. The aim of the work is to validate the performances in term of accuracy, precision and seamlessness behavior of the low-cost UWB technology available today. The results shown an overall accuracy of about 60 cm considering the entire path walked, both outdoor and indoors