Defining accuracy in the use of Kinect v2 for exercise monitoring

Woolford, Kirk

doi:10.1145/2790994.2791002

Cited by 11 publications

(7 citation statements)

References 14 publications

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“…It might be argued that there was a low consistency between the two systems in the study. Woolford et al [24] used the Qualisys ProReflex system and reflective markers to assess Microsoft Kinect v2 accuracy for monitoring physical activities. However, Qualisys ProReflex cameras emit 880 nm strobe, which might still contribute as an active noise source in the Kinect v2 recordings.…”

Section: Discussionmentioning

confidence: 99%

“…Although several studies evaluated the validity and reliability of the Microsoft Kinect v2 skeleton estimation using markerbased motion capture systems as a golden standard system [19]- [27], none of these studies investigated or reported any distortion in the estimated joint positions. The majority of these studies employed Vicon [19], [20], [33], [34], [21], [26]- [32], BTS SMART-DX [22], [35], or Qualisys [24], [36], [37] motion capture systems that all utilize reflective markers. Microsoft Kinect v2 estimates the depth information based on time-of-flight (ToF) principle using infrared (IR) emitters and detector [38].…”

Section: Introductionmentioning

confidence: 99%

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Influence of a Marker-Based Motion Capture System on the Performance of Microsoft Kinect v2 Skeleton Algorithm

et al. 2019

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Microsoft Kinect sensors are being widely used as low-cost marker-less motion capture systems in various kinematic studies. Previous studies investigated the reliability and validity of Microsoft Kinect sensors by employing marker-based motion capture systems. Both systems employ IR emitters and detectors to track human posture and physical activities. This paper hypothesizes that the motion capture systems may interfere with Microsoft Kinect One sensor and influence the sensor's performance in tracking the skeleton. Hence, this study investigated the impact of a motion capture system on the Microsoft Kinect v2 skeleton algorithm using a mannequin in the presence of eight Qualisys Oqus 300/310 cameras and retroreflective markers. It was found that the motion capture system introduced a destructive impact on the Microsoft Kinect v2 skeleton tracking algorithm. In addition, it was observed that retroreflective markers placed near the joints caused the Microsoft Kinect v2 to give an incorrect reading of estimate the joint position. The motion capture cameras thus caused a timevarying distortion of the Microsoft Kinect estimate of the joint position. It is believed that the inference can be reduced by decreasing the number of markers and avoiding facing the motion capture cameras in sight of Microsoft Kinect v2.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Influence of a Marker-Based Motion Capture System on the Performance of Microsoft Kinect v2 Skeleton Algorithm

et al. 2019

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“…Human body data can be obtained with sufficient accuracy without contact with a special marker on the human body. Woolford [17] suggests that such a system, the Kinect V2, may be useable compare to a traditional clinical system, in a healthcare environment because the target person does not need to put on any marker device so that tracking would be done without making physical contact with that person. That is, the skeleton can be recognized cheaply with sufficient accuracy using Kinect V2.…”

Section: Kinect V2mentioning

confidence: 99%

Privacy-aware Remote Monitoring System by Skeleton Recognition

Nitta¹,

Murayama²

2019

Proceedings of the Annual Hawaii International Conference on System Sciences

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As the number of elderly people living alone increases, the need for remote monitoring system is also increasing. The system automatically checks the safety of the elderly and notifies the state to remote areas in case of anomalies. However, how to protect the privacy of the watched person becomes a problem. We propose that skeleton recognition technology is useful to monitor people with high accuracy while protecting the privacy. It can be used not only to investigate his/her posture and motion, but also to selectively analyze the voice emitted by himself/herself. We developed a system that combines skeleton recognition and selective speech recognition by the audio direction. In this paper, we will explain the improvement of our system and report some experiment results.

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“…Camera-based tracking systems are accurate enough to recognize gestures and body movements (e.g., Microsoft Kinect v.2 has an accuracy of +=1cm [14]). They are not designed, however, to preserve identities -unless they are used in combination with facerecognition algorithms.…”

Section: Identity-preserving Tracking For Multiple Peoplementioning

confidence: 99%

Time travelers

Cafaro

Ress

2016

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct

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Open-air museums may encompass structures, buildings, sites, and other types of objects and artifacts that span across space and, because these objects were built and/or used during multiple periods of significance, across time. The multiplicity of storylines can confuse visitors. Thus, this paper introduces Somewhere in Time, a novel installation that integrates a combination of technologies with historic content that allows users to explore both time and space across museum structures/sites. We describe our work conceptualizing and designing a personalized, interactive map (Time Travelers) that allows visitors to explore complex narratives across both time and space.

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Defining accuracy in the use of Kinect v2 for exercise monitoring

Cited by 11 publications

References 14 publications

Influence of a Marker-Based Motion Capture System on the Performance of Microsoft Kinect v2 Skeleton Algorithm

Influence of a Marker-Based Motion Capture System on the Performance of Microsoft Kinect v2 Skeleton Algorithm

Privacy-aware Remote Monitoring System by Skeleton Recognition

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