3-D Audio in Mobile Communication Devices: Methods for Mobile Head-Tracking

Future generations of mobile communication devices will serve more and more as multimedia platforms capable of reproducing high quality audio. In order to achieve a 3-D sound perception the reproduction quality of audio via headphones can be significantly increased by applying binaural technology. To be independent of individual head-related transfer functions (HRTFs) and to guarantee a good performance for all listeners, an adaptation of the synthesized sound field to the listener's head movements is required. In this article several methods of head-tracking for mobile communication devices are presented and compared. A system for testing the identified methods is set up and experiments are performed to evaluate the prosand cons of each method. The implementation of such a device in a 3-D audio system is described and applications making use of such a system are identified and discussed.

Head Tracking Based Avatar Control for Virtual Environment Teamwork Training

Virtual environments (VE) are gaining in popularity and are increasingly used for teamwork training purposes, e.g., for medical teams. One shortcoming of modern VEs is that nonverbal communication channels, essential for teamwork, are not supported well. We address this issue by using an inexpensive webcam to track the user's head. This tracking information is used to control the head movement of the user's avatar, thereby conveying head gestures and adding a nonverbal communication channel. We conducted a user study investigating the influence of head tracking based avatar control on the perceived realism of the VE and on the performance of a surgical teamwork training scenario. Our results show that head tracking positively influences the perceived realism of the VE and the communication, but has no major influence on the training outcome.

Street crossing behavior in younger and older pedestrians: an eye- and head-tracking study

BACKGROUND: Crossing a street can be a very difficult task for older pedestrians. With increased age and potential cognitive decline, older people take the decision to cross a street primarily based on vehicles' distance, and not on their speed. Furthermore, older pedestrians tend to overestimate their own walking speed, and could not adapt it according to the traffic conditions. Pedestrians' behavior is often tested using virtual reality. Virtual reality presents the advantage of being safe, cost-effective, and allows using standardized test conditions. METHODS: This paper describes an observational study with older and younger adults. Street crossing behavior was investigated in 18 healthy, younger and 18 older subjects by using a virtual reality setting. The aim of the study was to measure behavioral data (such as eye and head movements) and to assess how the two age groups differ in terms of number of safe street crossings, virtual crashes, and missed street crossing opportunities. Street crossing behavior, eye and head movements, in older and younger subjects, were compared with non-parametric tests. RESULTS: The results showed that younger pedestrians behaved in a more secure manner while crossing a street, as compared to older people. The eye and head movements analysis revealed that older people looked more at the ground and less at the other side of the street to cross. CONCLUSIONS: The less secure behavior in street crossing found in older pedestrians could be explained by their reduced cognitive and visual abilities, which, in turn, resulted in difficulties in the decision-making process, especially under time pressure. Decisions to cross a street are based on the distance of the oncoming cars, rather than their speed, for both groups. Older pedestrians look more at their feet, probably because of their need of more time to plan precise stepping movement and, in turn, pay less attention to the traffic. This might help to set up guidelines for improving senior pedestrians' safety, in terms of speed limits, road design, and mixed physical-cognitive trainings.

Stereo-Based Head Pose Tracking Using Iterative Closest Point and Normal Flow Constraint

In this text, we present two stereo-based head tracking techniques along with a fast 3D model acquisition system. The first tracking technique is a robust implementation of stereo-based head tracking designed for interactive environments with uncontrolled lighting. We integrate fast face detection and drift reduction algorithms with a gradient-based stereo rigid motion tracking technique. Our system can automatically segment and track a user's head under large rotation and illumination variations. Precision and usability of this approach are compared with previous tracking methods for cursor control and target selection in both desktop and interactive room environments. The second tracking technique is designed to improve the robustness of head pose tracking for fast movements. Our iterative hybrid tracker combines constraints from the ICP (Iterative Closest Point) algorithm and normal flow constraint. This new technique is more precise for small movements and noisy depth than ICP alone, and more robust for large movements than the normal flow constraint alone. We present experiments which test the accuracy of our approach on sequences of real and synthetic stereo images. The 3D model acquisition system we present quickly aligns intensity and depth images, and reconstructs a textured 3D mesh. 3D views are registered with shape alignment based on our iterative hybrid tracker. We reconstruct the 3D model using a new Cubic Ray Projection merging algorithm which takes advantage of a novel data structure: the linked voxel space. We present experiments to test the accuracy of our approach on 3D face modelling using real-time stereo images.

Analysis of eye and head coordination in a visual peripheral recognition task

Coordinated eye and head movements simultaneously occur to scan the visual world for relevant targets. However, measuring both eye and head movements in experiments allowing natural head movements may be challenging. This paper provides an approach to study eye-head coordination: First, we demonstra- te the capabilities and limits of the eye-head tracking system used, and compare it to other technologies. Second, a beha- vioral task is introduced to invoke eye-head coordination. Third, a method is introduced to reconstruct signal loss in video- based oculography caused by cornea reflection artifacts in order to extend the tracking range. Finally, parameters of eye- head coordination are identified using EHCA (eye-head co- ordination analyzer), a MATLAB software which was developed to analyze eye-head shifts. To demonstrate the capabilities of the approach, a study with 11 healthy subjects was performed to investigate motion behavior. The approach presented here is discussed as an instrument to explore eye-head coordination, which may lead to further insights into attentional and motor symptoms of certain neurological or psychiatric diseases, e.g., schizophrenia.

Managing large scale virtual environments using portals

This article describes a technique for Large Scale Virtual Environments (LSVEs) partitioning in hexagon cells and using portal in the cell interfaces to reduce the number of messages on the network and the complexity of the virtual world. These environments usually demand a high volume of data that must be sent only to those users who needs the information [Greenhalgh, Benford 1997].

Navigating 3d Scatter Plots in Immersive Virtual Reality

Thesis (Master's)--University of Washington, 2016-01

An adaptive motion model for person tracking with instantaneous head-pose features

This letter presents novel behaviour-based tracking of people in low-resolution using instantaneous priors mediated by head-pose. We extend the Kalman Filter to adaptively combine motion information with an instantaneous prior belief about where the person will go based on where they are currently looking. We apply this new method to pedestrian surveillance, using automatically-derived head pose estimates, although the theory is not limited to head-pose priors. We perform a statistical analysis of pedestrian gazing behaviour and demonstrate tracking performance on a set of simulated and real pedestrian observations. We show that by using instantaneous `intentional' priors our algorithm significantly outperforms a standard Kalman Filter on comprehensive test data.

Real-time tracking system using C80 DSPs and a binocular robotic head

[EN]An active vision system to perform tracking of moving objects in real time is described. The main goal is to obtain a system integrating off-the-self components. These components includes a stereoscopic robotic-head, as active perception hardware; a DSP based board SDB C80, as massive data processor and image acquisition board; and finally, a Pentium PC running Windows NT that interconnects and manages the whole system. Real-time is achieved taking advantage of the special architecture of DSP. An evaluation of the performance is included.

Prospective motion correction of 3D echo-planar imaging data for functional MRI using optical tracking.

We evaluated the performance of an optical camera based prospective motion correction (PMC) system in improving the quality of 3D echo-planar imaging functional MRI data. An optical camera and external marker were used to dynamically track the head movement of subjects during fMRI scanning. PMC was performed by using the motion information to dynamically update the sequence's RF excitation and gradient waveforms such that the field-of-view was realigned to match the subject's head movement. Task-free fMRI experiments on five healthy volunteers followed a 2×2×3 factorial design with the following factors: PMC on or off; 3.0mm or 1.5mm isotropic resolution; and no, slow, or fast head movements. Visual and motor fMRI experiments were additionally performed on one of the volunteers at 1.5mm resolution comparing PMC on vs PMC off for no and slow head movements. Metrics were developed to quantify the amount of motion as it occurred relative to k-space data acquisition. The motion quantification metric collapsed the very rich camera tracking data into one scalar value for each image volume that was strongly predictive of motion-induced artifacts. The PMC system did not introduce extraneous artifacts for the no motion conditions and improved the time series temporal signal-to-noise by 30% to 40% for all combinations of low/high resolution and slow/fast head movement relative to the standard acquisition with no prospective correction. The numbers of activated voxels (p<0.001, uncorrected) in both task-based experiments were comparable for the no motion cases and increased by 78% and 330%, respectively, for PMC on versus PMC off in the slow motion cases. The PMC system is a robust solution to decrease the motion sensitivity of multi-shot 3D EPI sequences and thereby overcome one of the main roadblocks to their widespread use in fMRI studies.

Accuracy and Precision of Head Motion Information in Multi-Channel Free Induction Decay Navigators for Magnetic Resonance Imaging.

Free induction decay (FID) navigators were found to qualitatively detect rigid-body head movements, yet it is unknown to what extent they can provide quantitative motion estimates. Here, we acquired FID navigators at different sampling rates and simultaneously measured head movements using a highly accurate optical motion tracking system. This strategy allowed us to estimate the accuracy and precision of FID navigators for quantification of rigid-body head movements. Five subjects were scanned with a 32-channel head coil array on a clinical 3T MR scanner during several resting and guided head movement periods. For each subject we trained a linear regression model based on FID navigator and optical motion tracking signals. FID-based motion model accuracy and precision was evaluated using cross-validation. FID-based prediction of rigid-body head motion was found to be with a mean translational and rotational error of 0.14±0.21 mm and 0.08±0.13(°) , respectively. Robust model training with sub-millimeter and sub-degree accuracy could be achieved using 100 data points with motion magnitudes of ±2 mm and ±1(°) for translation and rotation. The obtained linear models appeared to be subject-specific as inter-subject application of a "universal" FID-based motion model resulted in poor prediction accuracy. The results show that substantial rigid-body motion information is encoded in FID navigator signal time courses. Although, the applied method currently requires the simultaneous acquisition of FID signals and optical tracking data, the findings suggest that multi-channel FID navigators have a potential to complement existing tracking technologies for accurate rigid-body motion detection and correction in MRI.

Low cost eye tracking for human-machine interfacing

One of the main challenges for developers of new human-computer interfaces is to provide a more natural way of interacting with computer systems, avoiding excessive use of hand and finger movements. In this way, also a valuable alternative communication pathway is provided to people suffering from motor disabilities. This paper describes the construction of a low cost eye tracker using a fixed head setup. Therefore a webcam, laptop and an infrared lighting source were used together with a simple frame to fix the head of the user. Furthermore, detailed information on the various image processing techniques used for filtering the centre of the pupil and different methods to calculate the point of gaze are discussed. An overall accuracy of 1.5 degrees was obtained while keeping the hardware cost of the device below 100 euros.

Quantitative analysis of accuracy of an inertial/acoustic 6DOF tracking system in motion

An increasing number of neuroscience experiments are using virtual reality to provide a more immersive and less artificial experimental environment. This is particularly useful to navigation and three-dimensional scene perception experiments. Such experiments require accurate real-time tracking of the observer's head in order to render the virtual scene. Here, we present data on the accuracy of a commonly used six degrees of freedom tracker (Intersense IS900) when it is moved in ways typical of virtual reality applications. We compared the reported location of the tracker with its location computed by an optical tracking method. When the tracker was stationary, the root mean square error in spatial accuracy was 0.64 mm. However, we found that errors increased over ten-fold (up to 17 mm) when the tracker moved at speeds common in virtual reality applications. We demonstrate that the errors we report here are predominantly due to inaccuracies of the IS900 system rather than the optical tracking against which it was compared. (c) 2006 Elsevier B.V. All rights reserved.

Group stochastic search for object detection and tracking

A technique is presented for locating and tracking objects in cluttered environments. Agents are randomly distributed across the image, and subsequently grouped around targets. Each agent uses a weightless neural network and a histogram intersection technique to score its location. The system has been used to locate and track a head in 320x240 resolution video at up to 15fps.