MetaSpace II: Object and full-body tracking for interaction and navigation in social VR

MetaSpace II (MS2) is a social Virtual Reality (VR) system where multiple users can not only see and hear but also interact with each other, grasp and manipulate objects, walk around in space, and get tactile feedback. MS2 allows walking in physical space by tracking each user's skeleton in real-time and allows users to feel by employing passive haptics i.e., when users touch or manipulate an object in the virtual world, they simultaneously also touch or manipulate a corresponding object in the physical world. To enable these elements in VR, MS2 creates a correspondence in spatial layout and object placement by building the virtual world on top of a 3D scan of the real world. Through the association between the real and virtual world, users are able to walk freely while wearing a head-mounted device, avoid obstacles like walls and furniture, and interact with people and objects. Most current virtual reality (VR) environments are designed for a single user experience where interactions with virtual objects are mediated by hand-held input devices or hand gestures. Additionally, users are only shown a representation of their hands in VR floating in front of the camera as seen from a first person perspective. We believe, representing each user as a full-body avatar that is controlled by natural movements of the person in the real world (see Figure 1d), can greatly enhance believability and a user's sense immersion in VR.Comment: 10 pages, 9 figures. Video: http://living.media.mit.edu/projects/metaspace-ii

Real Time Animation of Virtual Humans: A Trade-off Between Naturalness and Control

Virtual humans are employed in many interactive applications using 3D virtual environments, including (serious) games. The motion of such virtual humans should look realistic (or ‘natural’) and allow interaction with the surroundings and other (virtual) humans. Current animation techniques differ in the trade-off they offer between motion naturalness and the control that can be exerted over the motion. We show mechanisms to parametrize, combine (on different body parts) and concatenate motions generated by different animation techniques. We discuss several aspects of motion naturalness and show how it can be evaluated. We conclude by showing the promise of combinations of different animation paradigms to enhance both naturalness and control

Artimate: an articulatory animation framework for audiovisual speech synthesis

We present a modular framework for articulatory animation synthesis using speech motion capture data obtained with electromagnetic articulography (EMA). Adapting a skeletal animation approach, the articulatory motion data is applied to a three-dimensional (3D) model of the vocal tract, creating a portable resource that can be integrated in an audiovisual (AV) speech synthesis platform to provide realistic animation of the tongue and teeth for a virtual character. The framework also provides an interface to articulatory animation synthesis, as well as an example application to illustrate its use with a 3D game engine. We rely on cross-platform, open-source software and open standards to provide a lightweight, accessible, and portable workflow.Comment: Workshop on Innovation and Applications in Speech Technology (2012

Radar and RGB-depth sensors for fall detection: a review

This paper reviews recent works in the literature on the use of systems based on radar and RGB-Depth (RGB-D) sensors for fall detection, and discusses outstanding research challenges and trends related to this research field. Systems to detect reliably fall events and promptly alert carers and first responders have gained significant interest in the past few years in order to address the societal issue of an increasing number of elderly people living alone, with the associated risk of them falling and the consequences in terms of health treatments, reduced well-being, and costs. The interest in radar and RGB-D sensors is related to their capability to enable contactless and non-intrusive monitoring, which is an advantage for practical deployment and users’ acceptance and compliance, compared with other sensor technologies, such as video-cameras, or wearables. Furthermore, the possibility of combining and fusing information from The heterogeneous types of sensors is expected to improve the overall performance of practical fall detection systems. Researchers from different fields can benefit from multidisciplinary knowledge and awareness of the latest developments in radar and RGB-D sensors that this paper is discussing

MoSculp: Interactive Visualization of Shape and Time

We present a system that allows users to visualize complex human motion via 3D motion sculptures---a representation that conveys the 3D structure swept by a human body as it moves through space. Given an input video, our system computes the motion sculptures and provides a user interface for rendering it in different styles, including the options to insert the sculpture back into the original video, render it in a synthetic scene or physically print it. To provide this end-to-end workflow, we introduce an algorithm that estimates that human's 3D geometry over time from a set of 2D images and develop a 3D-aware image-based rendering approach that embeds the sculpture back into the scene. By automating the process, our system takes motion sculpture creation out of the realm of professional artists, and makes it applicable to a wide range of existing video material. By providing viewers with 3D information, motion sculptures reveal space-time motion information that is difficult to perceive with the naked eye, and allow viewers to interpret how different parts of the object interact over time. We validate the effectiveness of this approach with user studies, finding that our motion sculpture visualizations are significantly more informative about motion than existing stroboscopic and space-time visualization methods.Comment: UIST 2018. Project page: http://mosculp.csail.mit.edu

A framework for realistic 3D tele-immersion

Meeting, socializing and conversing online with a group of people using teleconferencing systems is still quite differ- ent from the experience of meeting face to face. We are abruptly aware that we are online and that the people we are engaging with are not in close proximity. Analogous to how talking on the telephone does not replicate the experi- ence of talking in person. Several causes for these differences have been identified and we propose inspiring and innova- tive solutions to these hurdles in attempt to provide a more realistic, believable and engaging online conversational expe- rience. We present the distributed and scalable framework REVERIE that provides a balanced mix of these solutions. Applications build on top of the REVERIE framework will be able to provide interactive, immersive, photo-realistic ex- periences to a multitude of users that for them will feel much more similar to having face to face meetings than the expe- rience offered by conventional teleconferencing systems

Going Deeper into Action Recognition: A Survey

Understanding human actions in visual data is tied to advances in complementary research areas including object recognition, human dynamics, domain adaptation and semantic segmentation. Over the last decade, human action analysis evolved from earlier schemes that are often limited to controlled environments to nowadays advanced solutions that can learn from millions of videos and apply to almost all daily activities. Given the broad range of applications from video surveillance to human-computer interaction, scientific milestones in action recognition are achieved more rapidly, eventually leading to the demise of what used to be good in a short time. This motivated us to provide a comprehensive review of the notable steps taken towards recognizing human actions. To this end, we start our discussion with the pioneering methods that use handcrafted representations, and then, navigate into the realm of deep learning based approaches. We aim to remain objective throughout this survey, touching upon encouraging improvements as well as inevitable fallbacks, in the hope of raising fresh questions and motivating new research directions for the reader

Piggybacking on an Autonomous Hauler: Business Models Enabling a System-of-Systems Approach to Mapping an Underground Mine

With ever-increasing productivity targets in mining operations, there is a growing interest in mining automation. In future mines, remote-controlled and autonomous haulers will operate underground guided by LiDAR sensors. We envision reusing LiDAR measurements to maintain accurate mine maps that would contribute to both safety and productivity. Extrapolating from a pilot project on reliable wireless communication in Boliden's Kankberg mine, we propose establishing a system-of-systems (SoS) with LIDAR-equipped haulers and existing mapping solutions as constituent systems. SoS requirements engineering inevitably adds a political layer, as independent actors are stakeholders both on the system and SoS levels. We present four SoS scenarios representing different business models, discussing how development and operations could be distributed among Boliden and external stakeholders, e.g., the vehicle suppliers, the hauling company, and the developers of the mapping software. Based on eight key variation points, we compare the four scenarios from both technical and business perspectives. Finally, we validate our findings in a seminar with participants from the relevant stakeholders. We conclude that to determine which scenario is the most promising for Boliden, trade-offs regarding control, costs, risks, and innovation must be carefully evaluated.Comment: Preprint of industry track paper accepted for the 25th IEEE International Conference on Requirements Engineering (RE'17