1,567 research outputs found

    A multi-modal dance corpus for research into real-time interaction between humans in online virtual environments

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    We present a new, freely available, multimodal corpus for research into, amongst other areas, real-time realistic interaction between humans in online virtual environments. The specific corpus scenario focuses on an online dance class application scenario where students, with avatars driven by whatever 3D capture technology are locally available to them, can learn choerographies with teacher guidance in an online virtual ballet studio. As the data corpus is focused on this scenario, it consists of student/teacher dance choreographies concurrently captured at two different sites using a variety of media modalities, including synchronised audio rigs, multiple cameras, wearable inertial measurement devices and depth sensors. In the corpus, each of the several dancers perform a number of fixed choreographies, which are both graded according to a number of specific evaluation criteria. In addition, ground-truth dance choreography annotations are provided. Furthermore, for unsynchronised sensor modalities, the corpus also includes distinctive events for data stream synchronisation. Although the data corpus is tailored specifically for an online dance class application scenario, the data is free to download and used for any research and development purposes

    Architecture and applications of the FingerMouse: a smart stereo camera for wearable computing HCI

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    In this paper we present a visual input HCI system for wearable computers, the FingerMouse. It is a fully integrated stereo camera and vision processing system, with a specifically designed ASIC performing stereo block matching at 5Mpixel/s (e.g. QVGA 320ร—240at 30fps) and a disparity range of 47, consuming 187mW (78mW in the ASIC). It is button-sized (43mmร—18mm) and can be worn on the body, capturing the user's hand and processing in real-time its coordinates as well as a 1-bit image of the hand segmented from the background. Alternatively, the system serves as a smart depth camera, delivering foreground segmentation and tracking, depth maps and standard images, with a processing latency smaller than 1ms. This paper describes the FingerMouse functionality and its applications, and how the specific architecture outperforms other systems in size, latency and power consumptio

    Requirement analysis and sensor specifications โ€“ First version

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    In this first version of the deliverable, we make the following contributions: to design the WEKIT capturing platform and the associated experience capturing API, we use a methodology for system engineering that is relevant for different domains such as: aviation, space, and medical and different professions such as: technicians, astronauts, and medical staff. Furthermore, in the methodology, we explore the system engineering process and how it can be used in the project to support the different work packages and more importantly the different deliverables that will follow the current. Next, we provide a mapping of high level functions or tasks (associated with experience transfer from expert to trainee) to low level functions such as: gaze, voice, video, body posture, hand gestures, bio-signals, fatigue levels, and location of the user in the environment. In addition, we link the low level functions to their associated sensors. Moreover, we provide a brief overview of the state-of-the-art sensors in terms of their technical specifications, possible limitations, standards, and platforms. We outline a set of recommendations pertaining to the sensors that are most relevant for the WEKIT project taking into consideration the environmental, technical and human factors described in other deliverables. We recommend Microsoft Hololens (for Augmented reality glasses), MyndBand and Neurosky chipset (for EEG), Microsoft Kinect and Lumo Lift (for body posture tracking), and Leapmotion, Intel RealSense and Myo armband (for hand gesture tracking). For eye tracking, an existing eye-tracking system can be customised to complement the augmented reality glasses, and built-in microphone of the augmented reality glasses can capture the expertโ€™s voice. We propose a modular approach for the design of the WEKIT experience capturing system, and recommend that the capturing system should have sufficient storage or transmission capabilities. Finally, we highlight common issues associated with the use of different sensors. We consider that the set of recommendations can be useful for the design and integration of the WEKIT capturing platform and the WEKIT experience capturing API to expedite the time required to select the combination of sensors which will be used in the first prototype.WEKI

    ์ธ๊ฐ„ ๊ธฐ๊ณ„ ์ƒํ˜ธ์ž‘์šฉ์„ ์œ„ํ•œ ๊ฐ•๊ฑดํ•˜๊ณ  ์ •ํ™•ํ•œ ์†๋™์ž‘ ์ถ”์  ๊ธฐ์ˆ  ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ๊ธฐ๊ณ„ํ•ญ๊ณต๊ณตํ•™๋ถ€, 2021.8. ์ด๋™์ค€.Hand-based interface is promising for realizing intuitive, natural and accurate human machine interaction (HMI), as the human hand is main source of dexterity in our daily activities. For this, the thesis begins with the human perception study on the detection threshold of visuo-proprioceptive conflict (i.e., allowable tracking error) with or without cutantoues haptic feedback, and suggests tracking error specification for realistic and fluidic hand-based HMI. The thesis then proceeds to propose a novel wearable hand tracking module, which, to be compatible with the cutaneous haptic devices spewing magnetic noise, opportunistically employ heterogeneous sensors (IMU/compass module and soft sensor) reflecting the anatomical properties of human hand, which is suitable for specific application (i.e., finger-based interaction with finger-tip haptic devices). This hand tracking module however loses its tracking when interacting with, or being nearby, electrical machines or ferromagnetic materials. For this, the thesis presents its main contribution, a novel visual-inertial skeleton tracking (VIST) framework, that can provide accurate and robust hand (and finger) motion tracking even for many challenging real-world scenarios and environments, for which the state-of-the-art technologies are known to fail due to their respective fundamental limitations (e.g., severe occlusions for tracking purely with vision sensors; electromagnetic interference for tracking purely with IMUs (inertial measurement units) and compasses; and mechanical contacts for tracking purely with soft sensors). The proposed VIST framework comprises a sensor glove with multiple IMUs and passive visual markers as well as a head-mounted stereo camera; and a tightly-coupled filtering-based visual-inertial fusion algorithm to estimate the hand/finger motion and auto-calibrate hand/glove-related kinematic parameters simultaneously while taking into account the hand anatomical constraints. The VIST framework exhibits good tracking accuracy and robustness, affordable material cost, light hardware and software weights, and ruggedness/durability even to permit washing. Quantitative and qualitative experiments are also performed to validate the advantages and properties of our VIST framework, thereby, clearly demonstrating its potential for real-world applications.์† ๋™์ž‘์„ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•œ ์ธํ„ฐํŽ˜์ด์Šค๋Š” ์ธ๊ฐ„-๊ธฐ๊ณ„ ์ƒํ˜ธ์ž‘์šฉ ๋ถ„์•ผ์—์„œ ์ง๊ด€์„ฑ, ๋ชฐ์ž…๊ฐ, ์ •๊ตํ•จ์„ ์ œ๊ณตํ•ด์ค„ ์ˆ˜ ์žˆ์–ด ๋งŽ์€ ์ฃผ๋ชฉ์„ ๋ฐ›๊ณ  ์žˆ๊ณ , ์ด๋ฅผ ์œ„ํ•ด ๊ฐ€์žฅ ํ•„์ˆ˜์ ์ธ ๊ธฐ์ˆ  ์ค‘ ํ•˜๋‚˜๊ฐ€ ์† ๋™์ž‘์˜ ๊ฐ•๊ฑดํ•˜๊ณ  ์ •ํ™•ํ•œ ์ถ”์  ๊ธฐ์ˆ  ์ด๋‹ค. ์ด๋ฅผ ์œ„ํ•ด ๋ณธ ํ•™์œ„๋…ผ๋ฌธ์—์„œ๋Š” ๋จผ์ € ์‚ฌ๋žŒ ์ธ์ง€์˜ ๊ด€์ ์—์„œ ์† ๋™์ž‘ ์ถ”์  ์˜ค์ฐจ์˜ ์ธ์ง€ ๋ฒ”์œ„๋ฅผ ๊ทœ๋ช…ํ•œ๋‹ค. ์ด ์˜ค์ฐจ ์ธ์ง€ ๋ฒ”์œ„๋Š” ์ƒˆ๋กœ์šด ์† ๋™์ž‘ ์ถ”์  ๊ธฐ์ˆ  ๊ฐœ๋ฐœ ์‹œ ์ค‘์š”ํ•œ ์„ค๊ณ„ ๊ธฐ์ค€์ด ๋  ์ˆ˜ ์žˆ์–ด ์ด๋ฅผ ํ”ผํ—˜์ž ์‹คํ—˜์„ ํ†ตํ•ด ์ •๋Ÿ‰์ ์œผ๋กœ ๋ฐํžˆ๊ณ , ํŠนํžˆ ์†๋ ์ด‰๊ฐ ์žฅ๋น„๊ฐ€ ์žˆ์„๋•Œ ์ด ์ธ์ง€ ๋ฒ”์œ„์˜ ๋ณ€ํ™”๋„ ๋ฐํžŒ๋‹ค. ์ด๋ฅผ ํ† ๋Œ€๋กœ, ์ด‰๊ฐ ํ”ผ๋“œ๋ฐฑ์„ ์ฃผ๋Š” ๊ฒƒ์ด ๋‹ค์–‘ํ•œ ์ธ๊ฐ„-๊ธฐ๊ณ„ ์ƒํ˜ธ์ž‘์šฉ ๋ถ„์•ผ์—์„œ ๋„๋ฆฌ ์—ฐ๊ตฌ๋˜์–ด ์™”์œผ๋ฏ€๋กœ, ๋จผ์ € ์†๋ ์ด‰๊ฐ ์žฅ๋น„์™€ ํ•จ๊ป˜ ์‚ฌ์šฉํ•  ์ˆ˜ ์žˆ๋Š” ์† ๋™์ž‘ ์ถ”์  ๋ชจ๋“ˆ์„ ๊ฐœ๋ฐœํ•œ๋‹ค. ์ด ์†๋ ์ด‰๊ฐ ์žฅ๋น„๋Š” ์ž๊ธฐ์žฅ ์™ธ๋ž€์„ ์ผ์œผ์ผœ ์ฐฉ์šฉํ˜• ๊ธฐ์ˆ ์—์„œ ํ”ํžˆ ์‚ฌ์šฉ๋˜๋Š” ์ง€์ž๊ธฐ ์„ผ์„œ๋ฅผ ๊ต๋ž€ํ•˜๋Š”๋ฐ, ์ด๋ฅผ ์ ์ ˆํ•œ ์‚ฌ๋žŒ ์†์˜ ํ•ด๋ถ€ํ•™์  ํŠน์„ฑ๊ณผ ๊ด€์„ฑ ์„ผ์„œ/์ง€์ž๊ธฐ ์„ผ์„œ/์†Œํ”„ํŠธ ์„ผ์„œ์˜ ์ ์ ˆํ•œ ํ™œ์šฉ์„ ํ†ตํ•ด ํ•ด๊ฒฐํ•œ๋‹ค. ์ด๋ฅผ ํ™•์žฅํ•˜์—ฌ ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š”, ์ด‰๊ฐ ์žฅ๋น„ ์ฐฉ์šฉ ์‹œ ๋ฟ ์•„๋‹ˆ๋ผ ๋ชจ๋“  ์žฅ๋น„ ์ฐฉ์šฉ / ํ™˜๊ฒฝ / ๋ฌผ์ฒด์™€์˜ ์ƒํ˜ธ์ž‘์šฉ ์‹œ์—๋„ ์‚ฌ์šฉ ๊ฐ€๋Šฅํ•œ ์ƒˆ๋กœ์šด ์† ๋™์ž‘ ์ถ”์  ๊ธฐ์ˆ ์„ ์ œ์•ˆํ•œ๋‹ค. ๊ธฐ์กด์˜ ์† ๋™์ž‘ ์ถ”์  ๊ธฐ์ˆ ๋“ค์€ ๊ฐ€๋ฆผ ํ˜„์ƒ (์˜์ƒ ๊ธฐ๋ฐ˜ ๊ธฐ์ˆ ), ์ง€์ž๊ธฐ ์™ธ๋ž€ (๊ด€์„ฑ/์ง€์ž๊ธฐ ์„ผ์„œ ๊ธฐ๋ฐ˜ ๊ธฐ์ˆ ), ๋ฌผ์ฒด์™€์˜ ์ ‘์ด‰ (์†Œํ”„ํŠธ ์„ผ์„œ ๊ธฐ๋ฐ˜ ๊ธฐ์ˆ ) ๋“ฑ์œผ๋กœ ์ธํ•ด ์ œํ•œ๋œ ํ™˜๊ฒฝ์—์„œ ๋ฐ–์— ์‚ฌ์šฉํ•˜์ง€ ๋ชปํ•œ๋‹ค. ์ด๋ฅผ ์œ„ํ•ด ๋งŽ์€ ๋ฌธ์ œ๋ฅผ ์ผ์œผํ‚ค๋Š” ์ง€์ž๊ธฐ ์„ผ์„œ ์—†์ด ์ƒ๋ณด์ ์ธ ํŠน์„ฑ์„ ์ง€๋‹ˆ๋Š” ๊ด€์„ฑ ์„ผ์„œ์™€ ์˜์ƒ ์„ผ์„œ๋ฅผ ์œตํ•ฉํ•˜๊ณ , ์ด๋•Œ ์ž‘์€ ๊ณต๊ฐ„์— ๋‹ค ์ž์œ ๋„์˜ ์›€์ง์ž„์„ ๊ฐ–๋Š” ์† ๋™์ž‘์„ ์ถ”์ ํ•˜๊ธฐ ์œ„ํ•ด ๋‹ค์ˆ˜์˜ ๊ตฌ๋ถ„๋˜์ง€ ์•Š๋Š” ๋งˆ์ปค๋“ค์„ ์‚ฌ์šฉํ•œ๋‹ค. ์ด ๋งˆ์ปค์˜ ๊ตฌ๋ถ„ ๊ณผ์ • (correspondence search)๋ฅผ ์œ„ํ•ด ๊ธฐ์กด์˜ ์•ฝ๊ฒฐํ•ฉ (loosely-coupled) ๊ธฐ๋ฐ˜์ด ์•„๋‹Œ ๊ฐ•๊ฒฐํ•ฉ (tightly-coupled ๊ธฐ๋ฐ˜ ์„ผ์„œ ์œตํ•ฉ ๊ธฐ์ˆ ์„ ์ œ์•ˆํ•˜๊ณ , ์ด๋ฅผ ํ†ตํ•ด ์ง€์ž๊ธฐ ์„ผ์„œ ์—†์ด ์ •ํ™•ํ•œ ์† ๋™์ž‘์ด ๊ฐ€๋Šฅํ•  ๋ฟ ์•„๋‹ˆ๋ผ ์ฐฉ์šฉํ˜• ์„ผ์„œ๋“ค์˜ ์ •ํ™•์„ฑ/ํŽธ์˜์„ฑ์— ๋ฌธ์ œ๋ฅผ ์ผ์œผํ‚ค๋˜ ์„ผ์„œ ๋ถ€์ฐฉ ์˜ค์ฐจ / ์‚ฌ์šฉ์ž์˜ ์† ๋ชจ์–‘ ๋“ฑ์„ ์ž๋™์œผ๋กœ ์ •ํ™•ํžˆ ๋ณด์ •ํ•œ๋‹ค. ์ด ์ œ์•ˆ๋œ ์˜์ƒ-๊ด€์„ฑ ์„ผ์„œ ์œตํ•ฉ ๊ธฐ์ˆ  (Visual-Inertial Skeleton Tracking (VIST)) ์˜ ๋›ฐ์–ด๋‚œ ์„ฑ๋Šฅ๊ณผ ๊ฐ•๊ฑด์„ฑ์ด ๋‹ค์–‘ํ•œ ์ •๋Ÿ‰/์ •์„ฑ ์‹คํ—˜์„ ํ†ตํ•ด ๊ฒ€์ฆ๋˜์—ˆ๊ณ , ์ด๋Š” VIST์˜ ๋‹ค์–‘ํ•œ ์ผ์ƒํ™˜๊ฒฝ์—์„œ ๊ธฐ์กด ์‹œ์Šคํ…œ์ด ๊ตฌํ˜„ํ•˜์ง€ ๋ชปํ•˜๋˜ ์† ๋™์ž‘ ์ถ”์ ์„ ๊ฐ€๋Šฅ์ผ€ ํ•จ์œผ๋กœ์จ, ๋งŽ์€ ์ธ๊ฐ„-๊ธฐ๊ณ„ ์ƒํ˜ธ์ž‘์šฉ ๋ถ„์•ผ์—์„œ์˜ ๊ฐ€๋Šฅ์„ฑ์„ ๋ณด์—ฌ์ค€๋‹ค.1 Introduction 1 1.1. Motivation 1 1.2. Related Work 5 1.3. Contribution 12 2 Detection Threshold of Hand Tracking Error 16 2.1. Motivation 16 2.2. Experimental Environment 20 2.2.1. Hardware Setup 21 2.2.2. Virtual Environment Rendering 23 2.2.3. HMD Calibration 23 2.3. Identifying the Detection Threshold of Tracking Error 26 2.3.1. Experimental Setup 27 2.3.2. Procedure 27 2.3.3. Experimental Result 31 2.4. Enlarging the Detection Threshold of Tracking Error by Haptic Feedback 31 2.4.1. Experimental Setup 31 2.4.2. Procedure 32 2.4.3. Experimental Result 34 2.5. Discussion 34 3 Wearable Finger Tracking Module for Haptic Interaction 38 3.1. Motivation 38 3.2. Development of Finger Tracking Module 42 3.2.1. Hardware Setup 42 3.2.2. Tracking algorithm 45 3.2.3. Calibration method 48 3.3. Evaluation for VR Haptic Interaction Task 50 3.3.1. Quantitative evaluation of FTM 50 3.3.2. Implementation of Wearable Cutaneous Haptic Interface 51 3.3.3. Usability evaluation for VR peg-in-hole task 53 3.4. Discussion 57 4 Visual-Inertial Skeleton Tracking for Human Hand 59 4.1. Motivation 59 4.2. Hardware Setup and Hand Models 62 4.2.1. Human Hand Model 62 4.2.2. Wearable Sensor Glove 62 4.2.3. Stereo Camera 66 4.3. Visual Information Extraction 66 4.3.1. Marker Detection in Raw Images 68 4.3.2. Cost Function for Point Matching 68 4.3.3. Left-Right Stereo Matching 69 4.4. IMU-Aided Correspondence Search 72 4.5. Filtering-based Visual-Inertial Sensor Fusion 76 4.5.1. EKF States for Hand Tracking and Auto-Calibration 78 4.5.2. Prediction with IMU Information 79 4.5.3. Correction with Visual Information 82 4.5.4. Correction with Anatomical Constraints 84 4.6. Quantitative Evaluation for Free Hand Motion 87 4.6.1. Experimental Setup 87 4.6.2. Procedure 88 4.6.3. Experimental Result 90 4.7. Quantitative and Comparative Evaluation for Challenging Hand Motion 95 4.7.1. Experimental Setup 95 4.7.2. Procedure 96 4.7.3. Experimental Result 98 4.7.4. Performance Comparison with Existing Methods for Challenging Hand Motion 101 4.8. Qualitative Evaluation for Real-World Scenarios 105 4.8.1. Visually Complex Background 105 4.8.2. Object Interaction 106 4.8.3. Wearing Fingertip Cutaneous Haptic Devices 109 4.8.4. Outdoor Environment 111 4.9. Discussion 112 5 Conclusion 116 References 124 Abstract (in Korean) 139 Acknowledgment 141๋ฐ•

    A gaze-contingent framework for perceptually-enabled applications in healthcare

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    Patient safety and quality of care remain the focus of the smart operating room of the future. Some of the most influential factors with a detrimental effect are related to suboptimal communication among the staff, poor flow of information, staff workload and fatigue, ergonomics and sterility in the operating room. While technological developments constantly transform the operating room layout and the interaction between surgical staff and machinery, a vast array of opportunities arise for the design of systems and approaches, that can enhance patient safety and improve workflow and efficiency. The aim of this research is to develop a real-time gaze-contingent framework towards a "smart" operating suite, that will enhance operator's ergonomics by allowing perceptually-enabled, touchless and natural interaction with the environment. The main feature of the proposed framework is the ability to acquire and utilise the plethora of information provided by the human visual system to allow touchless interaction with medical devices in the operating room. In this thesis, a gaze-guided robotic scrub nurse, a gaze-controlled robotised flexible endoscope and a gaze-guided assistive robotic system are proposed. Firstly, the gaze-guided robotic scrub nurse is presented; surgical teams performed a simulated surgical task with the assistance of a robot scrub nurse, which complements the human scrub nurse in delivery of surgical instruments, following gaze selection by the surgeon. Then, the gaze-controlled robotised flexible endoscope is introduced; experienced endoscopists and novice users performed a simulated examination of the upper gastrointestinal tract using predominately their natural gaze. Finally, a gaze-guided assistive robotic system is presented, which aims to facilitate activities of daily living. The results of this work provide valuable insights into the feasibility of integrating the developed gaze-contingent framework into clinical practice without significant workflow disruptions.Open Acces

    Software techniques for improving head mounted displays to create comfortable user experiences in virtual reality

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    Head Mounted Displays (HMDs) allow users to experience Virtual Reality (VR) with a great level of immersion. Advancements in hardware technologies have led to a reduction in cost of producing good quality VR HMDs bringing them out from research labs to consumer markets. However, the current generation of HMDs suffer from a few fundamental problems that can deter their widespread adoption. For this thesis, we explored two techniques to overcome some of the challenges of experiencing VR when using HMDs. When experiencing VR with HMDs strapped to your head, even simple physical tasks like drinking a beverage can be difficult and awkward. We explored mixed reality renderings that selectively incorporate the physical world into the virtual world for interactions with physical objects. We conducted a user study comparing four rendering techniques that balance immersion in the virtual world with ease of interaction with the physical world. Users of VR systems often experience vection, the perception of self-motion in the absence of any physical movement. While vection helps to improve presence in VR, it often leads to a form of motion sickness called cybersickness. Prior work has discovered that changing vection (changing the perceived speed or moving direction) causes more severe cybersickness than steady vection (walking at a constant speed or in a constant direction). Based on this idea, we tried to reduce cybersickness caused by character movements in a First Person Shooter (FPS) game in VR. We propose Rotation Blurring (RB), uniformly blurring the screen during rotational movements to reduce cybersickness. We performed a user study to evaluate the impact of RB in reducing cybersickness and found that RB led to an overall reduction in sickness levels of the participants and delayed its onset. Participants who experienced acute levels of cybersickness benefited significantly from this technique
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