Evaluasi Tingkat Akurasi Skeleton Tracking Dan Depth Sensor Pada Microsoft Kinect

There are a lot of studies that use Microsoft Kinect as its device to interact with the system, either stand-alone or integrated into other fields, such as robotics, medical, and entertainment. Of the many studies that have been conducted are to evaluate the performance of Microsoft Kinect. Features that are generally tested are the skeleton tracking, depth sensor, and others. This is generally done to determine the influence of certain factors on the performance of Microsoft Kinect or test the sensor feasibility when applied in certain circumstances. This research aimed to determine the effect the objects of everyday ordinary human beings held by the level of accuracy of execution on the Microsoft Kinect gesture so that it can become the information for future research in developing a system that uses Microsoft Kinect as its device of interaction. The system will be modeled using the Unified Modeling Language (UML) and implemented using C# programming language and Kinect for Windows SDK library. Results from this study is the percentage level of accuracy of execution gesture for every object that was tested on the system interface

A Feasibility Study on the Use of a Structured Light Depth-Camera for Three-Dimensional Body Measurements of Dairy Cows in Free-Stall Barns

Frequent checks on livestock\u2019s body growth can help reducing problems related to cow infertility or other welfare implications, and recognizing health\u2019s anomalies. In the last ten years, optical methods have been proposed to extract information on various parameters while avoiding direct contact with animals\u2019 body, generally causes stress. This research aims to evaluate a new monitoring system, which is suitable to frequently check calves and cow\u2019s growth through a three-dimensional analysis of their bodies\u2019 portions. The innovative system is based on multiple acquisitions from a low cost Structured Light Depth-Camera (Microsoft Kinect\u2122 v1). The metrological performance of the instrument is proved through an uncertainty analysis and a proper calibration procedure. The paper reports application of the depth camera for extraction of different body parameters. Expanded uncertainty ranging between 3 and 15 mm is reported in the case of ten repeated measurements. Coef\ufb01cients of determination R2> 0.84 and deviations lower than 6% from manual measurements where in general detected in the case of head size, hips distance, withers to tail length, chest girth, hips, and withers height. Conversely, lower performances where recognized in the case of animal depth (R2 = 0.74) and back slope (R2 = 0.12)

Kinect Range Sensing: Structured-Light versus Time-of-Flight Kinect

Recently, the new Kinect One has been issued by Microsoft, providing the next generation of real-time range sensing devices based on the Time-of-Flight (ToF) principle. As the first Kinect version was using a structured light approach, one would expect various differences in the characteristics of the range data delivered by both devices. This paper presents a detailed and in-depth comparison between both devices. In order to conduct the comparison, we propose a framework of seven different experimental setups, which is a generic basis for evaluating range cameras such as Kinect. The experiments have been designed with the goal to capture individual effects of the Kinect devices as isolatedly as possible and in a way, that they can also be adopted, in order to apply them to any other range sensing device. The overall goal of this paper is to provide a solid insight into the pros and cons of either device. Thus, scientists that are interested in using Kinect range sensing cameras in their specific application scenario can directly assess the expected, specific benefits and potential problem of either device.Comment: 58 pages, 23 figures. Accepted for publication in Computer Vision and Image Understanding (CVIU

Low-cost natural interface based on head movements

Sometimes people look for freedom in the virtual world. However, not all have the possibility to interact with a computer in the same way. Nowadays, almost every job requires interaction with computerized systems, so people with physical impairments do not have the same freedom to control a mouse, a keyboard or a touchscreen. In the last years, some of the government programs to help people with reduced mobility suffered a lot with the global economic crisis and some of those programs were even cut down to reduce costs. This paper focuses on the development of a touchless human-computer interface, which allows anyone to control a computer without using a keyboard, mouse or touchscreen. By reusing Microsoft Kinect sensors from old videogames consoles, a cost-reduced, easy to use, and open-source interface was developed, allowing control of a computer using only the head, eyes or mouth movements, with the possibility of complementary sound commands. There are already available similar commercial solutions, but they are so expensive that their price tends to be a real obstacle in their purchase; on the other hand, free solutions usually do not offer the freedom that people with reduced mobility need. The present solution tries to address these drawbacks. (C) 2015 Published by Elsevier B.V

Using data visualization to deduce faces expressions

Conferência Internacional, realizada na Turquia, de 6-8 de setembro de 2018.Collect and examine in real time multi modal sensor data of a human face, is an important problem in computer vision, with applications in medical and monitoring analysis, entertainment and security. Although its advances, there are still many open issues in terms of the identification of the facial expression. Different algorithms and approaches have been developed to find out patterns and characteristics that can help the automatic expression identification. One way to study data is through data visualizations. Data visualization turns numbers and letters into aesthetically pleasing visuals, making it easy to recognize patterns and find exceptions. In this article, we use information visualization as a tool to analyse data points and find out possible existing patterns in four different facial expressions.info:eu-repo/semantics/publishedVersio

Evaluation of Pose Tracking Accuracy in the First and Second Generations of Microsoft Kinect

Microsoft Kinect camera and its skeletal tracking capabilities have been embraced by many researchers and commercial developers in various applications of real-time human movement analysis. In this paper, we evaluate the accuracy of the human kinematic motion data in the first and second generation of the Kinect system, and compare the results with an optical motion capture system. We collected motion data in 12 exercises for 10 different subjects and from three different viewpoints. We report on the accuracy of the joint localization and bone length estimation of Kinect skeletons in comparison to the motion capture. We also analyze the distribution of the joint localization offsets by fitting a mixture of Gaussian and uniform distribution models to determine the outliers in the Kinect motion data. Our analysis shows that overall Kinect 2 has more robust and more accurate tracking of human pose as compared to Kinect 1.Comment: 10 pages, IEEE International Conference on Healthcare Informatics 2015 (ICHI 2015

Microsoft Kinect-based differences in lower limb kinematics and temporal characteristics of sit to walking phase of modified TUG test between men with and without Parkinson's disease

http://www.ester.ee/record=b476770