Arm-pointing gesture interface using surrounded stereo cameras system

Yamamoto, Y.; Yoda, Ikushi; Sakaue, Katsuhiko

doi:10.1109/icpr.2004.1333934

Cited by 27 publications

(17 citation statements)

References 6 publications

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“…However, because it is still a difficult problem to extract these two small positions, there are many alternative methods for estimating the pointing direction; head-hand line [2,6,8], head-finger line [4,6,13], forearm direction [1,6,8], and head orientation [8,11] methods. Regarding the head orientation approach, this method does not use the hand position so we need to obtain more information to identify the target object, for example, speech recognition to obtain the object features [11].…”

Section: Related Workmentioning

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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Section: Related Workmentioning

confidence: 99%

“…Thus, we use the head-finger line method. However, these conventional methods [4,6,13] do not take individual ways into account. Some studies considered individual ways using regression models [3,5].…”

Section: Related Workmentioning

confidence: 99%

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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“…Yamamoto et al [10] realizes selection of appliances by arm pointing using multiple stereo cameras. Our method does not use stereo cameras but multiple monocular cameras to realize the 3D measurement of finger pointing.…”

Section: Stereo Visionmentioning

confidence: 99%

3D Measurement by Distributed Camera System for Constructing an Intelligent Room

Irie

Wada

Umeda

2007

2007 Fourth International Conference on Networked Sensing Systems

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Abstract-We are constructing an intelligent room in which an operator can control home appliances such as a TV set with intuitive gestures. In this paper, we discuss three dimensional (3D) measurement of the intelligent room using a distributed camera system. The room carries CCD cameras with pan, tilt, and zoom functions. An operator makes hand waving and the room detects it. 3D position of the waving hand is measured using the cameras, and then pan, tilt and zooming-up of the cameras are carried out with the 3D information. A hand region is extracted using the color information, and the operator's gestures are recognized. 3D Finger pointing to select an appliance is measured using the cameras. Experiments verify the effectiveness of the proposed 3D measurement methods.

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“…However, it is a challenging task to estimate the 3-D hand pointing direction automatically and reliably from streams of video data due to the great variety and adaptability of hand movement and the undistinguishable features of the joints on the hand. Some previous work shows success in hand detection and tracking using multi-colored gloves [27], depth-aware cameras [28], background subtraction [29], color-based detection [28], [30], stereovision-based approaches [31]- [33], or binary-pattern-based hand feature detection [34], [35]. However, the big challenge remains to accurately detect and track the hand in spite of various hand rotations.…”

Section: B Hand Detection and Trackingmentioning

confidence: 99%

A Multi-Gesture Interaction System Using a 3-D Iris Disk Model for Gaze Estimation and an Active Appearance Model for 3-D Hand Pointing

Reale

Canavan

Liu

et al. 2011

IEEE Trans. Multimedia

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Abstract-In this paper, we present a vision-based human-computer interaction system, which integrates control components using multiple gestures, including eye gaze, head pose, hand pointing, and mouth motions. To track head, eye, and mouth movements, we present a two-camera system that detects the face from a fixed, wide-angle camera, estimates a rough location for the eye region using an eye detector based on topographic features, and directs another active pan-tilt-zoom camera to focus in on this eye region. We also propose a novel eye gaze estimation approach for point-of-regard (POR) tracking on a viewing screen. To allow for greater head pose freedom, we developed a new calibration approach to find the 3-D eyeball location, eyeball radius, and fovea position. Moreover, in order to get the optical axis, we create a 3-D iris disk by mapping both the iris center and iris contour points to the eyeball sphere. We then rotate the fovea accordingly and compute the final, visual axis gaze direction. This part of the system permits natural, non-intrusive, pose-invariant POR estimation from a distance without resorting to infrared or complex hardware setups. We also propose and integrate a two-camera hand pointing estimation algorithm for hand gesture tracking in 3-D from a distance. The algorithms of gaze pointing and hand finger pointing are evaluated individually, and the feasibility of the entire system is validated through two interactive information visualization applications.Index Terms-Gaze estimation, hand tracking, human-computer interaction (HCI).

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Arm-pointing gesture interface using surrounded stereo cameras system

Cited by 27 publications

References 6 publications

An efficient method for human pointing estimation for robot interaction

An efficient method for human pointing estimation for robot interaction

3D Measurement by Distributed Camera System for Constructing an Intelligent Room

A Multi-Gesture Interaction System Using a 3-D Iris Disk Model for Gaze Estimation and an Active Appearance Model for 3-D Hand Pointing

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