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Mobile interactions Augmented by Wearable Computing: A Design Space and vision

INTERNATIONAL JOURNAL OF MOBILE human computer interaction 2016年第4期8卷 104-114页

作者： Schneegass, Stefan Olsson, Thomas Mayer, Sven van Laerhoven, Kristof Univ Stuttgart Human Comp Interact Grp Stuttgart Germany Tampere Univ Technol Unit Human CtrTechnol IHTE Tampere Finland Univ Stuttgart Sociocognit Syst Grp Niels Henze Stuttgart Germany Univ Freiburg Embedded Syst Lab Freiburg Germany

Wearable computing has a huge potential to shape the way we interact with mobile devices in the future. interaction with mobile devices is still mainly limited to visual output and tactile finger-based input. Despite the visions of next-generation mobile interaction, the hand-held form factor hinders new interaction techniques becoming commonplace. In contrast, wearable devices and sensors are intended for more continuous and close-to-body use. This makes it possible to design novel wearable-augmented mobile interaction methods - both explicit and implicit. For example, the EEG signal from a wearable breast strap could be used to identify user status and change the device state accordingly (implicit) and the optical tracking with a head-mounted camera could be used to recognize gestural input (explicit). In this paper, the authors outline the design space for how the existing and envisioned wearable devices and sensors could augment mobile interaction techniques. Based on designs and discussions in a recently organized workshop on the topic as well as other related work, the authors present an overview of this design space and highlight some use cases that underline the potential therein.

关键词： Design Space Mobile Devices Mobile interaction Wearable Computing

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Sign Language Recognition for Assisting the Deaf in Hospitals 7th

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7th International workshop on human Behavior Understanding (HBU)

作者： Camgoz, Necati Cihan Kindiroglu, Ahmet Alp Akarun, Lale Univ Surrey Surrey GU2 7XH England Bogazici Univ Dept Comp Engn Istanbul Turkey

ISBN: (纸本)9783319468433;9783319468426

In this study, a real-time, computer vision based sign language recognition system aimed at aiding hearing impaired users in a hospital setting has been developed. By directing them through a tree of questions, the system allows the user to state their purpose of visit by answering between four to six questions. The deaf user can use sign language to communicate with the system, which provides a written transcript of the exchange. A database collected from six users was used for the experiments. user independent tests without using the tree-based interaction scheme yield a 96.67% accuracy among 1257 sign samples belonging to 33 sign classes. The experiments evaluated the effectiveness of the system in terms of feature selection and spatio-temporal modelling. The combination of hand position and movement features modelled by Temporal Templates and classified by Random Decision Forests yielded the best results. The tree- based interaction scheme further increased the recognition performance to more than 97.88 %.

关键词： Sign language recognition Assistive computer vision human computer interaction

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Towards Declarative Programming and Querying in a Distributed Cyber-Physical System: The i-vision Case 2

Towards Declarative Programming and Querying in a Distribute...

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2nd International workshop on Modelling, Analysis, and Control of Complex CPS (CPS Data)

作者： Kaefer, Tobias Harth, Andreas Mamessier, Sebastien KIT Inst AIFB Karlsruhe Germany Airbus Grp Innovat Creat Design & Concepts Ctr Ottobrunn Germany

ISBN: (纸本)9781509011544

Cyber-Physical Systems that interconnect components of different vendors and knowledge domains bring together a multitude of data schemas and interaction paradigms. In the i-vision project, we integrate Virtual Reality technologies with human Factors analysis methods using Semantic Technologies to allow for improved aircraft cockpit design. In this paper, we present the case of the i-vision project, specifically the software the project develops, describe its architecture and show how we allow for integrated querying by connecting a flight simulator, a Virtual Reality engine, and a human Factors analysis tool. We use a gateway between the simulator part of the system, which follows the publish/subscribe paradigm, and the human Factors analysis part, which follows the REST architectural style. We model the data using Semantic Web languages, make the data available using web protocols, and integrate and query the data using a rule engine for Linked Data.

关键词： Gateways (computer networks)

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Video Coding Layer Optimization For Target Detection

Video Coding Layer Optimization For Target Detection

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IEEE Applied Imagery Pattern Recognition workshop (AIPR)

作者： Pearlstein, Larry Aved, Alexander J. Patel, Ian Coll New Jersey Dept Elect & Comp Engn Ewing NJ 08618 USA Air Force Res Lab RIED Informat Directorate Rome NY USA

ISBN: (纸本)9781509032846

One challenge in a video surveillance system is the data rate required to represent digital video. Accordingly, the use of lossy video compression at a compression ratio of 100:1, or higher, is an essential part of any distributed live video system. The ensuing distortion can interfere with the goals of surveillance by confounding both human analysis and computer vision based processing. This paper investigates the interaction between the video coding layer and target detection, and proposes methods for improving overall system effectiveness. Previous related research has focused on joint optimization of the video coding layer where several streams share the same bandwidth. Our work is distinguished from prior studies in several area: we use Gradual Decoder Refresh, rather than the traditional GOP, to enable low delay and similarly avoid the use of B frames, which necessitate frame reordering. We extend the previous work by providing the ROC curves for the detection of foreground object motion, as a function of the quantization parameter. We also consider the H.265 video coding standard, in addition to H.264. We note some surprising findings. We show that H.265 can significantly underperform H.264 in terms of Area Under Curve vs. Bitrate, and that it is possible to produce large "false alarm" blobs for moving object detection, even for a stationary, relatively noise-free source coded at low QP.

关键词： video compression computer vision ROC AUC

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Wizard of Oz vs autonomous: Children's perception changes according to robot's operation condition

Wizard of Oz vs autonomous: Children's perception changes ac...

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IEEE International workshop on Robot and human Communication (ROMAN)

作者： Daniel Tozadore Adam Pinto Roseli Romero Gabriele Trovato Institute of Mathematical and Computer Sciences University of Sao Paulo Sao Carlos Brazil Graduate School of Advanced Science and Engineering Waseda University Tokyo Japan

The presence of robots in human lifestyle is no longer a distant reality, as robots are being employed in several fields, including educational purposes. However, most of the research in educational robotics does not use autonomous social behavior, but rather techniques like Wizard of Oz (WoZ). This paper presents the very first test in a school environment of a robotic architecture to control an autonomous system for educational interactions, evaluated from user's perspective when compared to a teleoperated situation. The architecture aims to manage three main communication robot resources - speech, vision and gesture - in an autonomous way and provide an interaction as acceptable as when someone controls the robot. The experiment was performed randomly assigning 82 students aged between 7 and 11 to interact with a NAO robot in two conditions of robot operation: autonomous and teleoperated. The results suggest that there is no significant difference between the conditions in user's enjoyment and system time response, but they decreased their perception regarding robot's intelligence after knowing about the teleoperation.

关键词： Autonomous systems Robot sensing systems Time factors Service robots Atmospheric measurements

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Multimodal Approach for Cognitive Task Performance Prediction from Body Postures, Facial Expressions and EEG Signal

Multimodal Approach for Cognitive Task Performance Predictio...

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workshop on Modeling Cognitive Processes from Multimodal Data (MCPMD)

作者： Babu, Ashwin Ramesh Rajavenkatanarayanan, Akilesh Brady, James Robert Makedon, Fillia Univ Texas Arlington Heracleia Lab Dept Comp Sci & Engn Arlington TX 76019 USA

ISBN: (纸本)9781450360722

Recent developments in computer vision and the emergence of wearable sensors have opened opportunities for the development of advanced and sophisticated techniques to enable multi-modal user assessment and personalized training which is important in educational, industrial training and rehabilitation applications. They have also paved way for the use of assistive robots to accurately assess human cognitive and physical skills. Assessment and training cannot be generalized as the requirement varies for every person and for every application. The ability of the system to adapt to the individual's needs and performance is essential for its effectiveness. In this paper, the focus is on task performance prediction which is an important parameter to consider for personalization. Several research works focus on how to predict task performance based on physiological and behavioral data. In this work, we follow a multi-modal approach where the system collects information from different modalities to predict performance based on (a) user's emotional state recognized from facial expressions(Behavioral data), (b) user's emotional state from body postures(Behavioral data) (c) task performance from EEG signals (Physiological data) while the person performs a robot-based cognitive task. This multi-modal approach of combining physiological data and behavioral data produces the highest accuracy of 87.5 percent, which outperforms the accuracy of prediction extracted from any single modality. In particular, this approach is useful in finding associations between facial expressions, body postures and brain signals while a person performs a cognitive task.

关键词： Body pose estimation Facial expression recognition EEG Convolutional Neural Networks Task engagement Cognitive assessment Sequence learning Brain computer Interface (BCI) Behavior monitoring

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Crossmodal language grounding, learning, and teaching

Crossmodal language grounding, learning, and teaching

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2016 workshop on Cognitive Computation: Integrating Neural and Symbolic Approaches, CoCo 2016

作者： Heinrich, Stefan Weber, Cornelius Wermter, Stefan Xie, Ruobing Lin, Yankai Liu, Zhiyuan Department of Informatics Knowledge Technology Group University of Hamburg Vogt-Koelln Str. 30 Hamburg22527 Germany Department of Computer Science and Technology Natural Language Processing Lab Tsinghua University Room 4-506 FIT Building Beijing100084 China

The human brain as one of the most complex dynamic systems enables us to communicate and externalise information by natural language. Despite extensive research, human-like communication with interactive robots is not yet possible, because we have not yet fully understood the mechanistic characteristics of the crossmodal binding between language, actions, and visual sensation that enable humans to acquire and use natural language. In this position paper we present vision- and action-embodied language learning research as part of a project investigating multi-modal learning. Our research endeavour includes to develop a) a cortical neural-network model that learns to ground language into crossmodal embodied perception and b) a knowledge-based teaching framework to bootstrap and scale-up the language acquisition to a level of language development in children of age up to two years. We embed this approach of internally grounding embodied experience and externally teaching abstract experience into the developmental robotics paradigm, by means of developing and employing a neurorobot that is capable of multisensory perception and interaction. The proposed research contributes to designing neuroscientific experiments on discovering crossmodal integration particularly in language processing and to constructing future robotic companions capable of natural communication. Copyright © 2016 for this paper by its authors.

关键词： Knowledge based systems

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Interface for augmenting spatial orientation of pilots via low cognitive load, peripheral vision 16

Interface for augmenting spatial orientation of pilots via l...

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13th ACM International Working Conference on Advanced Visual Interfaces, AVI 2016

作者： Tudoreanu, M. Eduard University of Arkansas at Little Rock 2801 S University Ave Little RockAR United States

ISBN: (纸本)9781450341318

Untrained pilots flying in reduced visibility are at a high risk of losing control of a small aircraft when using typical instrumentation. The reduced visibility makes it impossible for the pilot to see outside references, which increases the workload and cognitive stress on the pilot. An advanced visual interface that focuses on the use of non-central vision to allow pilots to feel rather than compute the basic spatial orientation of their small aircraft is presented in this paper. To promote our goal of reducing the pilot's cognitive load, the interface is controlled by a single input button in addition to the routine controls of the aircraft. The visual display aims to provide an immersive experience to the user, while not relying on the pilot's central focus of attention. Thus, the user can fully exploit and focus their attention on any available instrumentation and technology present in the cockpit, such as glass displays, synthetic or enhanced vision, GPS devices, with our interface offering an additional layer of awareness. The visualization provides both instantaneous and trend information to the user. A preliminary user study that revealed additional future improvements to the visual display is also briefly described. © 2016 Copyright held by the owner/author(s).

关键词： Cockpits (aircraft)

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human-Document interaction Systems -- A New Frontier for Document Image Analysis

Human-Document Interaction Systems -- A New Frontier for Doc...

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IAPR International workshop on Document Analysis Systems, DAS

作者： Dimosthenis Karatzas Vincent Poulain d'Andecy Marçal Rusiñol Antonio Chica Pere-Pau Vazquez Computer Vision Centre Universitat Autónoma de Barcelona Spain Yooz Aimargues France ViRVIG Group Universitat Politecnica de Barcelona Spain

All indications show that paper documents will not cede in favour of their digital counterparts, but will instead be used increasingly in conjunction with digital information. An open challenge is how to seamlessly link the physical with the digital -- how to continue taking advantage of the important affordances of paper, without missing out on digital functionality. This paper presents the authors' experience with developing systems for human-Document interaction based on augmented document interfaces and examines new challenges and opportunities arising for the document image analysis field in this area. The system presented combines state of the art camera-based document image analysis techniques with a range of complementary technologies to offer fluid human-Document interaction. Both fixed and nomadic setups are discussed that have gone through user testing in real-life environments, and use cases are presented that span the spectrum from business to educational applications.

关键词： Image analysis Hardware Databases Text analysis Cameras Libraries Mobile communication

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Low-cost scene modeling using a density function improves segmentation performance

Low-cost scene modeling using a density function improves se...

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IEEE International workshop on Robot and human Communication (ROMAN)

作者： Vivek Sharma Şule Yildirim-Yayilgan Luc Van Gool Faculty of Computer Science and Media Technology Norwegian University of Science and Technology in Gjovik Gjovik Norway ESAT-PSI VISICS iMinds KU Leuven Leuven Belgium ETH Computer Vision Laboratory Zürich Switzerland

We propose a low cost and effective way to combine a free simulation software and free CAD models for modeling human-object interaction in order to improve human & object segmentation. It is intended for research scenarios related to safe human-robot collaboration (SHRC) and interaction (SHRI) in the industrial domain. The task of human and object modeling has been used for detecting activity, and for inferring and predicting actions, different from those works, we do human and object modeling in order to learn interactions in RGB-D data for improving segmentation. For this purpose, we define a novel density function to model a three dimensional (3D) scene in a virtual environment (VREP). This density function takes into account various possible configurations of human-object and object-object relationships and interactions governed by their affordances. Using this function, we synthesize a large, realistic and highly varied synthetic RGB-D dataset that we use for training. We train a random forest classifier, and the pixelwise predictions obtained is integrated as a unary term in a pairwise conditional random fields (CRF). Our evaluation shows that modeling these interactions improves segmentation performance by ~7% in mean average precision and recall over state-of-the-art methods that ignore these interactions in real-world data. Our approach is computationally efficient, robust and can run real-time on consumer hardware.

关键词： Solid modeling Density functional theory Data models Three-dimensional displays Robot sensing systems Virtual environments

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