Hand posture and gesture recognition techniques for virtual reality applications: a survey

Sagayam, K. Martin; Hemanth, D. Jude

doi:10.1007/s10055-016-0301-0

Cited by 131 publications

(59 citation statements)

References 110 publications

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“…However, as previously discussed, gaze interaction remains a challenge at the intersection of technology, design, and human factors because it has several drawbacks in an input modality. Other efforts on recognizing facial expressions and gestures such as nodding as input exist, although they are mostly experimental [119][120][121]. Hand-held controllers ( Figure 5) are the most common current input devices, but text input is difficult with them.…”

Section: Interaction Designmentioning

confidence: 99%

Extended Reality in Spatial Sciences: A Review of Research Challenges and Future Directions

Çöltekin

Lochhead

Madden

et al. 2020

IJGI

163

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This manuscript identifies and documents unsolved problems and research challenges in the extended reality (XR) domain (i.e., virtual (VR), augmented (AR), and mixed reality (MR)). The manuscript is structured to include technology, design, and human factor perspectives. The text is visualization/display-focused, that is, other modalities such as audio, haptic, smell, and touch, while important for XR, are beyond the scope of this paper. We further narrow our focus to mainly geospatial research, with necessary deviations to other domains where these technologies are widely researched. The main objective of the study is to provide an overview of broader research challenges and directions in XR, especially in spatial sciences. Aside from the research challenges identified based on a comprehensive literature review, we provide case studies with original results from our own studies in each section as examples to demonstrate the relevance of the challenges in the current research. We believe that this paper will be of relevance to anyone who has scientific interest in extended reality, and/or uses these systems in their research.

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Section: Interaction Designmentioning

confidence: 99%

Extended Reality in Spatial Sciences: A Review of Research Challenges and Future Directions

Çöltekin

Lochhead

Madden

et al. 2020

IJGI

163

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“…HAR has become a hot scientific topic in computer vision community. It is involved in the development of many important applications such as human computer interaction (HCI) [65], virtual reality [164], security [171], video surveillance and home monitoring [14, 138, 145, 156-161, 163, 223]. Therefore, the wide range of the activity recognition methods is directly linked to the application domain to which they are implemented [145].…”

Section: Introductionmentioning

confidence: 99%

Vision-based human activity recognition: a survey

Beddiar

Nini

Sabokrou

et al. 2020

Multimed Tools Appl

304

117

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Human activity recognition (HAR) systems attempt to automatically identify and analyze human activities using acquired information from various types of sensors. Although several extensive review papers have already been published in the general HAR topics, the growing technologies in the field as well as the multi-disciplinary nature of HAR prompt the need for constant updates in the field. In this respect, this paper attempts to review and summarize the progress of HAR systems from the computer vision perspective. Indeed, most computer vision applications such as human computer interaction, virtual reality, security, video surveillance and home monitoring are highly correlated to HAR tasks. This establishes new trend and milestone in the development cycle of HAR systems. Therefore, the current survey aims to provide the reader with an up to date analysis of vision-based HAR related literature and recent progress in the field. At the same time, it will highlight the main challenges and future directions.

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“…lenge due to background noise, occlusions, and view angle, for example [6][7][8][9]. We propose making gesture recognition more accurate and robust with the use of a 2D Convolutional Neural Network (CNN) utilizing both color and depth information.…”

Section: Introductionmentioning

confidence: 99%

MagicHand: Interact with IoT Devices in Augmented Reality Environment

Sun

Armengol-Urpi

Kantareddy

et al. 2019

2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)

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We present an Augmented Reality (AR) visualization and interaction tool for users to control Internet of Things (IoT) devices with hand gestures. Today, smart IoT devices are becoming increasingly ubiquitous with diverse forms and functions, yet most user controls over them are still limited to mobile devices and web interfaces. Recently, AR has been developed rapidly, and provided immersive solutions to enhance user experience of applications in many fields. Its capability to create immersive interactions allows AR to improve the way smart devices are controlled via more direct visual feedback. In this paper, we create a functional prototype of one such system, enabling seamless interactions with sound and lighting systems through the use of augmented hand-controlled interaction panels. To interpret users' intentions, we implement a standard 2D convolution neural network (CNN) for real-time hand gesture recognition and deploy it within our system. Our prototype is also equipped with a simple but effective object detector which can identify target devices within a proper range by analyzing visual and geometric features. We evaluate the performance of our system qualitatively and quantitatively and demonstrate it on two smart devices.

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Hand posture and gesture recognition techniques for virtual reality applications: a survey

Cited by 131 publications

References 110 publications

Extended Reality in Spatial Sciences: A Review of Research Challenges and Future Directions

Extended Reality in Spatial Sciences: A Review of Research Challenges and Future Directions

Vision-based human activity recognition: a survey

MagicHand: Interact with IoT Devices in Augmented Reality Environment

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