Real-time 3D pointing gesture recognition for mobile robots with cascade HMM and particle filter

Park, Chang-Beom; Lee, Seong–Whan

doi:10.1016/j.imavis.2010.08.006

Cited by 61 publications

(39 citation statements)

References 25 publications

(35 reference statements)

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“…Moreover, he used pointing to identify an area on the screen to which an object should be moved. Instructions by gesture have subsequently been applied in robotics [9,16]. Often, speech commands are added to specify the intention of the gesture.…”

Section: Pointing Gesture Applicationsmentioning

confidence: 99%

Free-hand pointing for identification and interaction with distant objects

Rümelin

Marouane²,

Butz³

2013

Proceedings of the 5th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

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In this paper, we investigate pointing as a lightweight form of gestural interaction in cars. In a pre-study, we show the technical feasibility of reliable pointing detection with a depth camera by achieving a recognition rate of 96% in the lab. In a subsequent insitu study, we let drivers point to objects inside and outside of the car while driving through a city. In three usage scenarios, we studied how this influenced their driving objectively, as well as subjectively. Distraction from the driving task was compensated by a regulation of driving speed and did not have a negative influence on driving behaviour. Our participants considered pointing a desirable interaction technique in comparison to current controller-based interaction and identified a number of additional promising use cases for pointing in the car.

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Section: Pointing Gesture Applicationsmentioning

confidence: 99%

Free-hand pointing for identification and interaction with distant objects

Rümelin

Marouane²,

Butz³

2013

Proceedings of the 5th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

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“…This angular offset corresponds to vertical offset . If the user points at the object with just a small pointing gesture [9], this vertical offset is relatively large. Even in this case, our method can adapt to a small pointing gesture.…”

Section: Estimation Of the Angular Offsetmentioning

confidence: 99%

“…Note that, from the comparison of the accuracy among (a), (b), and (c) camera views, the highest level of accuracy is from (b) quarter view, and the accuracy is as about the same as that as (c) side view and (a) frontal view. Many conventional methods [1,2,4,6,9,10] captured the pointing gestures from a frontal camera. We assume that the easiest way is to detect the users from a frontal camera.…”

Section: Experimental Environmentmentioning

confidence: 99%

“…If these offsets become too great to ignore, the robot will fail to identify the position of the target object even if the robot is able to extract the eye and the fingertip positions precisely. For example, when the user points to the object with a small pointing gesture [9], these offsets tend to be greater. To overcome this problem, one solution is to adapt to the pointing gesture ways by using regression methods [3,5].…”

Section: Introductionmentioning

confidence: 99%

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An efficient method for human pointing estimation for robot interaction

Ueno

Naito

Chen

2014

2014 IEEE International Conference on Image Processing (ICIP)

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In this paper, we propose an efficient calibration method to estimate the pointing direction via a human pointing gesture to facilitate robot interaction. The ways in which pointing gestures are used by humans to indicate an object are individually diverse. In addition, people do not always point at the object carefully, which means there is a divergence between the line from the eye to the tip of the index finger and the line of sight. Hence, we focus on adapting to these individual ways of pointing to improve the accuracy of target object identification by means of an effective calibration process. We model these individual ways as two offsets, the horizontal offset and the vertical offset. After locating the head and fingertip positions, we learn these offsets for each individual through a training process with the person pointing at the camera. Experimental results show that our proposed method outperforms other conventional head-hand, head-fingertip, and eye-fingertipbased pointing recognition methods.

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“…Typical examples include: daily activities detection [1], medical rehabilitation and assistance [2], user identification and authentication [3], sign language interpretation [4], computer games [5], augmented reality [6], user interfaces [7] and robot control [8].…”

mentioning

confidence: 99%

Motion-Based Gesture Recognition Algorithms for Robot Manipulation

Marasović

Papić

Marasović

2015

International Journal of Advanced Robotic Systems

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The prevailing trend of integrating inertial sensors in consumer electronics devices has inspired research on new forms of human-computer interaction utilizing hand gestures, which may be set-up on mobile devices themselves. At present, motion gesture recognition is intensely studied, with various recognition techniques being employed and tested. This paper provides an in-depth, unbiased comparison of different algorithms used to recognize gestures based primarily on the single 3D accelerometer recordings. The study takes two of the most popular and arguably the best recognition methods currently in use -dynamic time warping and hidden Markov model -and sets them against a relatively novel approach founded on distance metric learning. The three selected algorithms are evaluated in terms of their overall performance, accuracy, training time, execution time and storage efficacy. The optimal algorithm is further implemented in a prototype user application, aimed to serve as an interface for controlling the motion of a toy robot via gestures made with a smartphone.

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Real-time 3D pointing gesture recognition for mobile robots with cascade HMM and particle filter

Cited by 61 publications

References 25 publications

Free-hand pointing for identification and interaction with distant objects

Free-hand pointing for identification and interaction with distant objects

An efficient method for human pointing estimation for robot interaction

Motion-Based Gesture Recognition Algorithms for Robot Manipulation

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