In this work, algorithms are developed and evaluated to de- tect physical activities from data acquired using five small biaxial ac- celerometers worn simultaneously on different parts of the body. Ac- celeration data was collected from 20 subjects without researcher su- pervision or observation. Subjects were asked to perform a sequence of everyday tasks but not told specifically where or how to do them. Mean, energy, frequency-domain entropy, and correlation of acceleration data was calculated and several classifiers using these features were tested. De- cision tree classifiers showed the best performance recognizing everyday activities with an overall accuracy rate of 84%. The results show that although some activities are recognized well with subject-independent training data, others appear to require subject-specific training data. The results suggest that multiple accelerometers aid in recognition because conjunctions in acceleration feature values can effectively discriminate many activities. With just two biaxial accelerometers - thigh and wrist - the recognition performance dropped only slightly. This is the first work to investigate performance of recognition algorithms with multiple, wire-free accelerometers on 20 activities using datasets annotated by the subjects themselves.

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Activity recognition from user-annotated acceleration data

We are on the verge of ubiquitously adopting Augmented Reality (AR) technologies to enhance our percep- tion and help us see, hear, and feel our environments in new and enriched ways. AR will support us in fields such as education, maintenance, design and reconnaissance, to name but a few. This paper describes the field of AR, including a brief definition and development history, the enabling technologies and their characteristics. It surveys the state of the art by reviewing some recent applications of AR technology as well as some known limitations regarding human factors in the use of AR systems that developers will need to overcome.

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A Survey of Augmented Reality Technologies, Applications and Limitations

The last 20 years have seen ever-increasing research activity in the field of human activity recognition. With activity recognition having considerably matured, so has the number of challenges in designing, implementing, and evaluating activity recognition systems. This tutorial aims to provide a comprehensive hands-on introduction for newcomers to the field of human activity recognition. It specifically focuses on activity recognition using on-body inertial sensors. We first discuss the key research challenges that human activity recognition shares with general pattern recognition and identify those challenges that are specific to human activity recognition. We then describe the concept of an Activity Recognition Chain (ARC) as a general-purpose framework for designing and evaluating activity recognition systems. We detail each component of the framework, provide references to related research, and introduce the best practice methods developed by the activity recognition research community. We conclude with the educational example problem of recognizing different hand gestures from inertial sensors attached to the upper and lower arm. We illustrate how each component of this framework can be implemented for this specific activity recognition problem and demonstrate how different implementations compare and how they impact overall recognition performance.

A tutorial on human activity recognition using body-worn inertial sensors

A Tutorial on Human Activity Recognition Using Body-Worn

Although Augmented Reality technology was first developed over forty years ago, there has been little survey work giving an overview of recent research in the field. This paper reviews the ten-year development of the work presented at the ISMAR conference and its predecessors with a particular focus on tracking, interaction and display research. It provides a roadmap for future augmented reality research which will be of great value to this relatively young field, and also for helping researchers decide which topics should be explored when they are beginning their own studies in the area.

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Trends in augmented reality tracking, interaction and display: A review of ten years of ISMAR

Head-worn display design is inherently an interdisciplinary subject fusing optical engineering, optical materials, optical coatings, electronics, manufacturing techniques, user interface design, computer science, human perception, and physiology for assessing these displays. This paper summarizes the state-of-the-art in head-worn display design (HWD) and development. This review is focused on the optical engineering aspects, divided into different sections to explore principles and applications. Building on the guiding fundamentals of optical design and engineering, the principles section includes a summary of microdisplay or laser sources, the Lagrange invariant for understanding the trade-offs in optical design of HWDs, modes of image presentation (i.e., monocular, biocular, and stereo) and operational modes such as optical and video see-through. A brief summary of the human visual system pertinent to the design of HWDs is provided. Two optical design forms, namely, pupil forming and non-pupil forming are discussed. We summarize the results from previous design work using aspheric, diffractive, or holographic elements to achieve compact and lightweight systems. The applications section is organized in terms of field of view requirements and presents a reasonable collection of past designs

Head-worn displays: a review

If a wearable device can register what the wearer is currently doing, it can anticipate and adjust its behavior to avoid redundant interaction with the user. However, the relevance and properties of the activities that should be recognized depend on both the application and the user. This requires an adaptive recognition of the activities where the user, instead of the designer, can teach the device what he/she is doing. As a case study we connected a pair of pants with accelerometers to a laptop to interpret the raw sensor data. Using a combination of machine learning techniques such as Kohonen maps and probabilistic models, we build a system that is able to learn activities while requiring minimal user attention.

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What shall we teach our pants

Short range communication systems and techniques are described. In an implementation an interrogator held near a person interrogates multiple transponders and receives information separately from the transponders. The interrogator and/or the transponders may be held in an article of clothing or in a personal effect of the person. The transponders may transmit identifying information and/or information associated with the states of the articles of clothing or personal effects of the person. Such a system enables the clothes worn by a person to communicate with a plurality of items and obtain useful information. In addition, a network system may be configured so that any particular transponder may communicate with another transponder or group of transponders of other locales to activate functions, cause actions or otherwise share data and/or information.

Short range communication system

We are proposing a novel optical see-through head- worn display that is capable of mutual occlusions. Mutual occlusion is an attribute of an augmented reality display where real objects can occlude virtual objects and virtual objects can occlude real objects. For a user to achieve the perception of indifference between the real and the virtual images superimposed on the real environment, mutual occlusion is a strongly desired attribute for certain applications. This paper presents a breakthrough in display hardware from a mobility (i.e. compactness), resolution, and a switching speed based criteria. Specifically, we focus on the research that is related to virtual objects being able to occlude real objects. The core of the system is a spatial light modulator (SLM) and polarization-based optics which allow us to block or pass certain parts of a scene which is viewed through the head-worn display. An objective lens images the scene onto the SLM and the modulated image is mapped back to the original scene via an eyepiece. We are combining computer generated imagery with the modulated version of the scene to form the final image a user would see.

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A Compact Optical See-Through Head-Worn Display with Occlusion Support

A local optical surface representation as a sum of basis functions is proposed and implemented. Specifically, we investigate the use of linear combination of Gaussians. The proposed approach is a local descriptor of shape and we show how such surfaces are optimized to represent rotationally non-symmetric surfaces as well as rotationally symmetric surfaces. As an optical design example, a single surface off-axis mirror with multiple fields is optimized, analyzed, and compared to existing shape descriptors. For the specific case of the single surface off-axis magnifier with a 3 mm pupil, >15mm eye relief, 24 degree diagonal full field of view, we found the linear combination of Gaussians surface to yield an 18.5% gain in the average MTF across 17 field points compared to a Zernike polynomial up to and including 10th order. The sum of local basis representation is not limited to circular apertures.

Ozan Cakmakci

Papers

Head-worn displays: a review

What shall we teach our pants

Short range communication system

A Compact Optical See-Through Head-Worn Display with Occlusion Support

Optimal local shape description for rotationally non-symmetric optical surface design and analysis.