Real-time pointing gesture recognition for an immersive environment

Kehl, Roland; Gool, Luc Van

doi:10.1109/afgr.2004.1301595

Cited by 56 publications

(36 citation statements)

References 15 publications

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“…[33]- [35]) and estimating the referred-to target has been addressed by several authors in recent years, aiming at applications in robotics (e.g. [36]- [39]), smart environments (e.g.…”

Section: Related Workmentioning

confidence: 99%

Saliency-based identification and recognition of pointed-at objects

Schauerte

Richarz

Fink

2010

2010 IEEE/RSJ International Conference on Intelligent Robots and Systems

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Abstract-When persons interact, non-verbal cues are used to direct the attention of persons towards objects of interest. Achieving joint attention this way is an important aspect of natural communication. Most importantly, it allows to couple verbal descriptions with the visual appearance of objects, if the referred-to object is non-verbally indicated. In this contribution, we present a system that utilizes bottom-up saliency and pointing gestures to efficiently identify pointed-at objects. Furthermore, the system focuses the visual attention by steering a pan-tilt-zoom camera towards the object of interest and thus provides a suitable model-view for SIFT-based recognition and learning. We demonstrate the practical applicability of the proposed system through experimental evaluation in different environments with multiple pointers and objects.

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“…[33]- [35]) and estimating the referred-to target has been addressed by several authors in recent years, aiming at applications in robotics (e.g. [36]- [39]), smart environments (e.g.…”

Section: Related Workmentioning

confidence: 99%

Saliency-based identification and recognition of pointed-at objects

Schauerte

Richarz

Fink

2010

2010 IEEE/RSJ International Conference on Intelligent Robots and Systems

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“…In the literature, line of sight or head-hand line are widely used for pointing direction recognition [15,13,16]. However, these methods may fail in some situations where people cannot raise their arms in the same level as eyes or fully stretch their arms.…”

Section: Pointing Direction Recognitionmentioning

confidence: 99%

“…In order This work is submitted to the invited session entitled "Learning and Control in Human-Robot Interaction". to extract pointing vectors from human body, head-hand line [15], wrist-hand line, and line of sight [16] were employed. A real-time visual system was proposed in [15], where color and disparity information was retrieved from a stereo camera and used to locate hands and head.…”

Section: Introductionmentioning

confidence: 99%

3D pointing gesture recognition for human-robot interaction

Lai

Wang

et al. 2016

2016 Chinese Control and Decision Conference (CCDC)

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Abstract:In this paper, a pointing gesture recognition method is proposed for human-robot interaction. The pointing direction of the human partner is obtained by extracting the joint coordinates and computing through vector calculations. 3D to 2D mapping is implemented to build a top-view 2D map with respect to the actual ground circumstance. Using this method, robot is able to interpret the human partner's 3D pointing gesture based on the coordinate information of his/her shoulder and hand. Besides this, speed control of robot can be achieved by adjusting the position of the human partner's hand relative to the head. The recognition performance and viability of the system are tested through quantitative experiments.

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“…Most of them try to fit an articulated body model to the 3D data [3,16], but fast tracking of such articulated structures is far from trivial. Kehl et al [11] propose to limit the number of gestures by detecting only pointing gestures. Leubner [14] also utilizes multi-view geometry in a back projected immersive wall but the system is limited to 8 frames per second.…”

Section: Nitionmentioning

confidence: 99%

On the usability of gesture interfaces in virtual reality environments

Cabral

Morimoto

Zuffo

2005

Proceedings of the 2005 Latin American Conference on Human-Computer Interaction - CLIHC '05

100

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This paper discusses several usability issues related to the use of gestures as an input mode in multimodal interfaces. The use of gestures has been suggested before as a natural solution for applications that require hands-free and notouch interaction with computers, such as in virtual reality (VR) environments. We introduce a simple but robust 2D computer vision based gesture recognition system that was successfully used for interaction in VR environments such as CAVEs and Powerwalls. This interface was tested under 3 different scenarios, as a regular pointing device in a GUI interface, as a navigation tool, and as a visualization tool. Our experiments show that the time to completion of simple pointing tasks is considerably slower when compared to a mouse and that its use during even short periods of time causes fatigue. Despite these drawbacks, the use of gestures as an alternative mode in multimodal interfaces offers several advantages, such as quick access to computing resources that might be embedded in the environment, using a natural and intuitive way, and that scales nicely to group and collaborative applications, where gestures can be used sporadically.

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Real-time pointing gesture recognition for an immersive environment

Abstract: We present an algorithm for the real-time

Cited by 56 publications

References 15 publications

Saliency-based identification and recognition of pointed-at objects

Saliency-based identification and recognition of pointed-at objects

3D pointing gesture recognition for human-robot interaction

On the usability of gesture interfaces in virtual reality environments

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