A Conceptual Image-Based Data Glove for Computer-Human Interaction

Data gloves are devices equipped with sensors that capture the movements of the hand of the user in order to select or manipulate objects in a virtual world. Data gloves were introduced three decades ago and since then have been used in many 3D interaction techniques. However, good data gloves are too expensive and only a few of them can perceive the full set of hand movements. In this paper we describe the design of an image-based data glove (IBDG) prototype suitable for finger sensible applications, like virtual objects manipulation and interaction approaches. The proposed device uses a camera to track visual markers at finger tips, and a software module tocompute the position of each finger tip and its joints in real-time. To evaluate our concept, we have built a prototype and tested it with 15 volunteers. We also discuss how to improve the engineering of the prototype, how to turn it into a low cost interaction device, as well as other relevant issues about this original concept

Using colocation to support human memory

The progress of health care in the western world has been marked by an increase in life expectancy. Advances in life expectancy have meant that more people are living with acute health problems, many of which are related to impairment of memory. This paper describes a pair of scenarios that use RFID to assist people who may suffer frommemory defects to extend their capability for independent living. We present our implementation of an RFID glove, describe its operation, and show how it enables the application scenarios

Wearable performance

This is the post-print version of the article. The official published version can be accessed from the link below - Copyright @ 2009 Taylor & FrancisWearable computing devices worn on the body provide the potential for digital interaction in the world. A new stage of computing technology at the beginning of the 21st Century links the personal and the pervasive through mobile wearables. The convergence between the miniaturisation of microchips (nanotechnology), intelligent textile or interfacial materials production, advances in biotechnology and the growth of wireless, ubiquitous computing emphasises not only mobility but integration into clothing or the human body. In artistic contexts one expects such integrated wearable devices to have the two-way function of interface instruments (e.g. sensor data acquisition and exchange) worn for particular purposes, either for communication with the environment or various aesthetic and compositional expressions. 'Wearable performance' briefly surveys the context for wearables in the performance arts and distinguishes display and performative/interfacial garments. It then focuses on the authors' experiments with 'design in motion' and digital performance, examining prototyping at the DAP-Lab which involves transdisciplinary convergences between fashion and dance, interactive system architecture, electronic textiles, wearable technologies and digital animation. The concept of an 'evolving' garment design that is materialised (mobilised) in live performance between partners originates from DAP Lab's work with telepresence and distributed media addressing the 'connective tissues' and 'wearabilities' of projected bodies through a study of shared embodiment and perception/proprioception in the wearer (tactile sensory processing). Such notions of wearability are applied both to the immediate sensory processing on the performer's body and to the processing of the responsive, animate environment. Wearable computing devices worn on the body provide the potential for digital interaction in the world. A new stage of computing technology at the beginning of the 21st Century links the personal and the pervasive through mobile wearables. The convergence between the miniaturisation of microchips (nanotechnology), intelligent textile or interfacial materials production, advances in biotechnology and the growth of wireless, ubiquitous computing emphasises not only mobility but integration into clothing or the human body. In artistic contexts one expects such integrated wearable devices to have the two-way function of interface instruments (e.g. sensor data acquisition and exchange) worn for particular purposes, either for communication with the environment or various aesthetic and compositional expressions. 'Wearable performance' briefly surveys the context for wearables in the performance arts and distinguishes display and performative/interfacial garments. It then focuses on the authors' experiments with 'design in motion' and digital performance, examining prototyping at the DAP-Lab which involves transdisciplinary convergences between fashion and dance, interactive system architecture, electronic textiles, wearable technologies and digital animation. The concept of an 'evolving' garment design that is materialised (mobilised) in live performance between partners originates from DAP Lab's work with telepresence and distributed media addressing the 'connective tissues' and 'wearabilities' of projected bodies through a study of shared embodiment and perception/proprioception in the wearer (tactile sensory processing). Such notions of wearability are applied both to the immediate sensory processing on the performer's body and to the processing of the responsive, animate environment

Multimodal Grounding for Language Processing

This survey discusses how recent developments in multimodal processing facilitate conceptual grounding of language. We categorize the information flow in multimodal processing with respect to cognitive models of human information processing and analyze different methods for combining multimodal representations. Based on this methodological inventory, we discuss the benefit of multimodal grounding for a variety of language processing tasks and the challenges that arise. We particularly focus on multimodal grounding of verbs which play a crucial role for the compositional power of language.Comment: The paper has been published in the Proceedings of the 27 Conference of Computational Linguistics. Please refer to this version for citations: https://www.aclweb.org/anthology/papers/C/C18/C18-1197

Design and Evaluation of Menu Systems for Immersive Virtual Environments

Interfaces for system control tasks in virtual environments (VEs) have not been extensively studied. This paper focuses on various types of menu systems to be used in such environments. We describe the design of the TULIP menu, a menu system using Pinch Gloves™, and compare it to two common alternatives: floating menus and pen and tablet menus. These three menus were compared in an empirical evaluation. The pen and tablet menu was found to be significantly faster, while users had a preference for TULIP. Subjective discomfort levels were also higher with the floating menus and pen and tablet

Comparison of input devices in an ISEE direct timbre manipulation task

The representation and manipulation of sound within multimedia systems is an important and currently under-researched area. The paper gives an overview of the authors' work on the direct manipulation of audio information, and describes a solution based upon the navigation of four-dimensional scaled timbre spaces. Three hardware input devices were experimentally evaluated for use in a timbre space navigation task: the Apple Standard Mouse, Gravis Advanced Mousestick II joystick (absolute and relative) and the Nintendo Power Glove. Results show that the usability of these devices significantly affected the efficacy of the system, and that conventional low-cost, low-dimensional devices provided better performance than the low-cost, multidimensional dataglove

Learning semantic sentence representations from visually grounded language without lexical knowledge

Current approaches to learning semantic representations of sentences often use prior word-level knowledge. The current study aims to leverage visual information in order to capture sentence level semantics without the need for word embeddings. We use a multimodal sentence encoder trained on a corpus of images with matching text captions to produce visually grounded sentence embeddings. Deep Neural Networks are trained to map the two modalities to a common embedding space such that for an image the corresponding caption can be retrieved and vice versa. We show that our model achieves results comparable to the current state-of-the-art on two popular image-caption retrieval benchmark data sets: MSCOCO and Flickr8k. We evaluate the semantic content of the resulting sentence embeddings using the data from the Semantic Textual Similarity benchmark task and show that the multimodal embeddings correlate well with human semantic similarity judgements. The system achieves state-of-the-art results on several of these benchmarks, which shows that a system trained solely on multimodal data, without assuming any word representations, is able to capture sentence level semantics. Importantly, this result shows that we do not need prior knowledge of lexical level semantics in order to model sentence level semantics. These findings demonstrate the importance of visual information in semantics