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

Reachable Workspace and Proximal Function Measures for Quantifying Upper Limb Motion.

There are a lack of quantitative measures for clinically assessing upper limb function. Conventional biomechanical performance measures are restricted to specialist labs due to hardware cost and complexity, while the resulting measurements require specialists for analysis. Depth cameras are low cost and portable systems that can track surrogate joint positions. However, these motions may not be biologically consistent, which can result in noisy, inaccurate movements. This paper introduces a rigid body modelling method to enforce biological feasibility of the recovered motions. This method is evaluated on an existing depth camera assessment: the reachable workspace (RW) measure for assessing gross shoulder function. As a rigid body model is used, position estimates of new proximal targets can be added, resulting in a proximal function (PF) measure for assessing a subject's ability to touch specific body landmarks. The accuracy, and repeatability of these measures is assessed on ten asymptomatic subjects, with and without rigid body constraints. This analysis is performed both on a low-cost depth camera system and a gold-standard active motion capture system. The addition of rigid body constraints was found to improve accuracy and concordance of the depth camera system, particularly in lateral reaching movements. Both RW and PF measures were found to be feasible candidates for clinical assessment, with future analysis needed to determine their ability to detect changes within specific patient populations

Bio-inspired Dynamic 3D Discriminative Skeletal Features for Human Action Recognition

Over the last few years, with the immense popularity of the Kinect, there has been renewed interest in developing methods for human gesture and action recognition from 3D data. A number of approaches have been proposed that ex-tract representative features from 3D depth data, a recon-structed 3D surface mesh or more commonly from the re-covered estimate of the human skeleton. Recent advances in neuroscience have discovered a neural encoding of static 3D shapes in primate infero-temporal cortex that can be represented as a hierarchy of medial axis and surface fea-tures. We hypothesize a similar neural encoding might also exist for 3D shapes in motion and propose a hierarchy of dynamic medial axis structures at several spatio-temporal scales that can be modeled using a set of Linear Dynami-cal Systems (LDSs). We then propose novel discriminative metrics for comparing these sets of LDSs for the task of hu-man activity recognition. Combined with simple classifica-tion frameworks, our proposed features and corresponding hierarchical dynamical models provide the highest human activity recognition rates as compared to state-of-the-art methods on several skeletal datasets. 1

Factors and conditions of functioning and development of modern regional socio-economic systems

Purpose: The purpose of this article is the systemic modernization of scientific ideas relating to the essential factors and conditions of functioning and development of regional socioeconomic systems. Design/Methodology/Approach: To substantiate the article about the possibility of overcoming the socio-economic stagnation and recession of the region's economy based on modernization of research tools and management of local and regional socio-economic processes using modern agglomerative technologies and methods. Findings: Finding lies in clarifying the arrangement, structure and importance of socioeconomic processes, factors and conditions of local, regional and interregional level that determine the effectiveness and sustainability of functioning of the economy. Practical Implications: Are determined by the possibility to use authors' scientific results for audit, evaluation and adjustment of regional socio-economic impacts, measures and development programs, used during designing, forecast and assessment of socio-economic and complex efficiency of local and regional socio-economic activeness in the cities and municipal areas. Originality / Value: It is substantiated by development of the theory and methodology of regional studies of socio-economic factors and conditions that determine long-term prospects of stable functioning and sustainable development of the regional economy on the basis of adaptation of the basic direction of the system and reproduction processes.peer-reviewe

Realistic and interactive high-resolution 4D environments for real-time surgeon and patient interaction

Copyright © 2016 John Wiley & Sons, Ltd. Background: Remote consultations that are realistic enough to be useful medically offer considerable clinical, logistical and cost benefits. Despite advances in virtual reality and vision hardware and software, these benefits are currently often unrealised. Method: The proposed approach combines high spatial and temporal resolution 3D and 2D machine vision with virtual reality techniques, in order to develop new environments and instruments that will enable realistic remote consultations and the generation of new types of useful clinical data. Results: New types of clinical data have been generated for skin analysis and respiration measurement; and the combination of 3D with 2D data was found to offer potential for the generation of realistic virtual consultations. Conclusion: An innovative combination of high resolution machine vision data and virtual reality online methods, promises to provide advanced functionality and significant medical benefits, particularly in regions where populations are dispersed or access to clinicians is limited. Copyright © 2016 John Wiley & Sons, Ltd