GESTURE RECOGNITION FOR PENCAK SILAT TAPAK SUCI REAL-TIME ANIMATION

The main target in this research is a design of a virtual martial arts training system in real-time and as a tool in learning martial arts independently using genetic algorithm methods and dynamic time warping. In this paper, it is still in the initial stages, which is focused on taking data sets of martial arts warriors using 3D animation and the Kinect sensor cameras, there are 2 warriors x 8 moves x 596 cases/gesture = 9,536 cases. Gesture Recognition Studies are usually distinguished: body gesture and hand and arm gesture, head and face gesture, and, all three can be studied simultaneously in martial arts pencak silat, using martial arts stance detection with scoring methods. Silat movement data is recorded in the form of oni files using the OpenNI ™ (OFW) framework and BVH (Bio Vision Hierarchical) files as well as plug-in support software on Mocap devices. Responsiveness is a measure of time responding to interruptions, and is critical because the system must be able to meet the demand

Real-time Assessment and Visual Feedback for Patient Rehabilitation Using Inertial Sensors

Rehabilitation exercises needs have been continuously increasing and have been projected to increase in future as well based on its demand for aging population, recovering from surgery, injury and illness and the living and working lifestyle of the people. This research aims to tackle one of the most critical issues faced by the exercise administers-Adherence or Non-Adherence to Home Exercise problems especially has been a significant issue resulting in extensive research on the psychological analysis of people involved. In this research, a solution is provided to increase the adherence of such programs through an automated real-time assessment with constant visual feedback providing a game like an environment and recording the same for analysis purposes. Inertial sensors like Accelerometer and Gyroscope has been used to implement a rule-based framework for human activity recognition for measuring the ankle joint angle. This system is also secure as it contains only the recordings of the data and the avatar that could be live fed or recorded for the treatment analysis purposes which could save time and cost. The results obtained after testing on four healthy human subjects shows that with proper implementation of rule parameters, good quality and quantity of the exercises can be assessed in real time

TiFEE : an input event-handling framework with touchless device support

Tese de mestrado integrado. Engenharia Informática e Computação. Universidade do Porto. Faculdade de Engenharia. 201

D3.1 Instructional Designs for Real-time Feedback

The main objective of METALOGUE is to produce a multimodal dialogue system that is able to implement an interactive behaviour that seems natural to users and is flexible enough to exploit the full potential of multimodal interaction. The METALOGUE system will be arranged in the context of educational use-case scenarios, i.e. for training active citizens (Youth Parliament) and call centre employees. This deliverable describes the intended real-time feedback and reflection in-action support to support the training. Real-time feedback informs learners how they perform key skills and enables them to monitor their progress and thus reflect in-action. This deliverable examines the theoretical considerations of reflection in-action, what type of data is available and should be used, the timing and type of real-time feedback and, finally, concludes with an instructional design blueprint giving a global outline of a set of tasks with stepwise increasing complexity and the feedback proposed.The underlying research project is partly funded by the METALOGUE project. METALOGUE is a Seventh Framework Programme collaborative project funded by the European Commission, grant agreement number: 611073 (http://www.metalogue.eu)

Camera Marker Networks for Pose Estimation and Scene Understanding in Construction Automation and Robotics.

The construction industry faces challenges that include high workplace injuries and fatalities, stagnant productivity, and skill shortage. Automation and Robotics in Construction (ARC) has been proposed in the literature as a potential solution that makes machinery easier to collaborate with, facilitates better decision-making, or enables autonomous behavior. However, there are two primary technical challenges in ARC: 1) unstructured and featureless environments; and 2) differences between the as-designed and the as-built. It is therefore impossible to directly replicate conventional automation methods adopted in industries such as manufacturing on construction sites. In particular, two fundamental problems, pose estimation and scene understanding, must be addressed to realize the full potential of ARC. This dissertation proposes a pose estimation and scene understanding framework that addresses the identified research gaps by exploiting cameras, markers, and planar structures to mitigate the identified technical challenges. A fast plane extraction algorithm is developed for efficient modeling and understanding of built environments. A marker registration algorithm is designed for robust, accurate, cost-efficient, and rapidly reconfigurable pose estimation in unstructured and featureless environments. Camera marker networks are then established for unified and systematic design, estimation, and uncertainty analysis in larger scale applications. The proposed algorithms' efficiency has been validated through comprehensive experiments. Specifically, the speed, accuracy and robustness of the fast plane extraction and the marker registration have been demonstrated to be superior to existing state-of-the-art algorithms. These algorithms have also been implemented in two groups of ARC applications to demonstrate the proposed framework's effectiveness, wherein the applications themselves have significant social and economic value. The first group is related to in-situ robotic machinery, including an autonomous manipulator for assembling digital architecture designs on construction sites to help improve productivity and quality; and an intelligent guidance and monitoring system for articulated machinery such as excavators to help improve safety. The second group emphasizes human-machine interaction to make ARC more effective, including a mobile Building Information Modeling and way-finding platform with discrete location recognition to increase indoor facility management efficiency; and a 3D scanning and modeling solution for rapid and cost-efficient dimension checking and concise as-built modeling.PHDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113481/1/cforrest_1.pd

Contextual game design: from interface development to human activity recognition

A dissertação focasse nos seguintes pontos: Criação de diferentes interfaces usando o sensor Kinect, para reablitação de pacientes com cancro de mama. E, reconhecimento de atividade humana (problema derivado aquando a criação das interfaces)

Designing a Foot Input System for Productive Work at a Standing Desk

In this thesis we present Tap-Kick-Click, a foot interaction system for controlling common desktop applications. This system enables computer workers to take healthy and productive breaks from using a keyboard and mouse and demonstrates foot interaction techniques which could be applied in other contexts. Our work supplements the existing literature on foot based interaction, as no published work has combined foot input with a standing desk or attempted control of conventional desktop applications. We describe two experiments to investigate questions about the human performance characteristics of foot input relevant to our application which were unanswered in the existing literature. These experiments investigated the effect of target size, direction and distance; the difference between dominant and non-dominant foot; the use of tapping and kicking interaction; and the impact of displaying or hiding a foot cursor. Based on our results we present a set of design guidelines including a suggested minimum target size; a recommendation to ignore foot dominance; and a preference ranking for direction and foot action. These design guidelines informed the design of Tap-Kick-Click, which we describe in detail. It uses a sensing technique using a Microsoft Kinect depth camera and a pair of augmented slippers capable of robustly sensing foot position, kicking and tapping. The primary interaction technique is based on combinations of foot action and directional tapping in a low-density target layout, supported by feedback and instructions presented in an always visible sidebar. This technique is supplemented with a system for selecting elements in a GUI, a high-density target layout for selecting items from a menu, and a help screen. We illustrate the usefulness of Tap-Kick-Click by describing how it can be used to control a web browser, a citation manager and a debugger. Finally, we present the results of a study conducted to evaluate whether new users could learn and use the system in a web browser context. The study demonstrated that users are successfully able to learn and use the system, along with providing areas for improvement.4 month