Hand gesture recognition with depth images: A review

Suarez, Jesus; Murphy, Robin R.

doi:10.1109/roman.2012.6343787

Cited by 317 publications

(151 citation statements)

References 34 publications

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“…5) It has been shown that the KINECT is able to on-line track and interpret body gestures (Biswas & Basu, 2011;Suarez & Murphy, 2012) and basic emotions (Zhang, Zhang, & Hossain, 2013;Piana, Staglianò, Odone, Verri, & Camurri, 2014), allowing for another dimension to be added to the dependent measures in a psycholinguistic experiment.…”

Section: Opportunities Offered By the Kinect For Research In Psycholimentioning

confidence: 99%

The Microsoft KINECT: A Novel Tool for Psycholinguistic Research

Verdonschot¹,

Guillemaud²,

Rabenarivo³

et al. 2015

OJML

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The Microsoft KINECT is a 3D sensing device originally developed for the XBOX. The Microsoft KINECT opens up many exciting new opportunities for conducting experimental research on human behavior. We investigated some of these possibilities within the field of psycholinguistics (specifically: language production) by creating software, using C#, allowing for the KINECT to be used in a typical psycholinguistic experimental setting. The results of a naming experiment using this software confirmed that the KINECT was able to measure the effects of a robust psycholinguistic variable (word frequency) on naming latencies. However, although the current version of the software is able to measure psycholinguistic variables of interest, we also discuss several points where the software can still stand to be improved. The main aim of this paper is to make the software freely available for assessment and use by the psycholinguistic community and to illustrate the KINECT as a potentially valuable tool for investigating human behavior, especially in the field of psycholinguistics.

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Section: Opportunities Offered By the Kinect For Research In Psycholimentioning

confidence: 99%

The Microsoft KINECT: A Novel Tool for Psycholinguistic Research

Verdonschot¹,

Guillemaud²,

Rabenarivo³

et al. 2015

OJML

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show abstract

“…Gesture recognition is a key aspect of Human-Computer-Interaction. There are countless researches focus on this advanced topic to create natural user interface and to improve user experiences by using simple and intuitive hand gestures for free-hand controller [2]. How to detect the hands, segment them from the background and recognize the gestures become great challenges.…”

Section: Introductionmentioning

confidence: 99%

Hand Gesture Recognition Using Appearance Features Based on 3D Point Cloud

Chong¹,

Huang²,

Pan³

2016

JSEA

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This paper presents a method for hand gesture recognition based on 3D point cloud. Digital image processing technology is used in this research. Based on the 3D point from depth camera, the system firstly extracts some raw data of the hand. After the data segmentation and preprocessing, three kinds of appearance features are extracted, including the number of stretched fingers, the angles between fingers and the gesture region's area distribution feature. Based on these features, the system implements the identification of the gestures by using decision tree method. The results of experiment demonstrate that the proposed method is pretty efficient to recognize common gestures with a high accuracy.

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“…Hands could be visually detected or tracked by a range of sensors [29], such as ego-centric/self-mounted cameras [30], stereo camera [31], or Kinect [32]. In this paper, we focus on hand detection and tracking solely based on a single, static camera feed, which is a non-invasive and low-cost solution, leading to a convenient, computer-vision-based system.…”

Section: Introductionmentioning

confidence: 99%

HD: Efficient Hand Detection and Tracking

Rouge

Shaikh

Olszewska

2016

Annals of Computer Science and Information Systems

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Abstract-Automated hand detection is useful for applications requiring reliable hand posture and hand gesture processing. Such applications include human-computer/human-robot interfaces for rehabilitation, serious games, or non-invasive medical diagnosis. Hence, in this paper, we focus on the design and development of a robust and fast hand detection and tracking (HD) system. The design of our HD system involved the study of the human skin colour and people's foreground properties, in order to merge these information for an efficient hand detection and tracking. Experiments have been carried out in real-world environment and have demonstrated the excellent performance of our HD system.

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Hand gesture recognition with depth images: A review

Cited by 317 publications

References 34 publications

The Microsoft KINECT: A Novel Tool for Psycholinguistic Research

The Microsoft KINECT: A Novel Tool for Psycholinguistic Research

Hand Gesture Recognition Using Appearance Features Based on 3D Point Cloud

HD: Efficient Hand Detection and Tracking

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