A computer vision system for on-screen item selection by finger pointing

Lee, M.S.; Weinshall, Daphna; Cohen‐Solal, Emmanuelle; Colmenarez, Antonio J.; Lyons, David M.

doi:10.1109/cvpr.2001.990643

Cited by 13 publications

(3 citation statements)

References 12 publications

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“…The ZombiBoard [9] and BrightBoard [13] are examples of extensions of classical 2D "point-and-click" style user interfaces to desktop/blackboard style interactions. [4], [8], [17] are also examples of projects motivated by natural interaction with digital environments. Zhang et al's Visual Panel [21] enables the use of arbitrary planar surfaces as 3D input devices.…”

Section: A Related Workmentioning

confidence: 99%

The 4D Touchpad: Unencumbered HCI With VICs

Corso

Burschka

Hager

2003

2003 Conference on Computer Vision and Pattern Recognition Workshop

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Abstract-We present a platform for human-machine interfaces that provides functionality for robust, unencumbered interaction: the 4D Touchpad (4DT). The goal is direct interaction with interface components through intuitive actions and gestures.The 4DT is based on the 3D-2D Projection-based mode of the VICs framework. The fundamental idea behind VICs is that expensive global image processing with user modeling and tracking is not necessary in general vision-based HCI. Instead, interface components operating under simple-tocomplex rules in local image regions provide more robust and less costly functionality with 3 spatial dimensions and 1 temporal dimension. A prototype realization of the 4DT platform is presented; it operates through a set of planar homographies with uncalibrated cameras.

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Section: A Related Workmentioning

confidence: 99%

The 4D Touchpad: Unencumbered HCI With VICs

Corso

Burschka

Hager

2003

2003 Conference on Computer Vision and Pattern Recognition Workshop

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“…However, it is a challenging task to estimate the 3D hand pointing direction automatically and reliably from the streams of video data due to the great variety and adaptability of hand movement and the undistinguishable hand features of the joint parts. Some previous work show the success in hand detection and tracking using multi-colored gloves [16] and depth-aware cameras [8], or background subtraction [14], color-based detection [7,8], stereo vision based [2,4,18] or binary pattern based [5,10] hand feature detection. However, the big challenge remains for accurate hand detection and tracking in terms of various hand rotations.…”

Section: Introductionmentioning

confidence: 99%

Hand Pointing Estimation for Human Computer Interaction Based on Two Orthogonal-Views

Canavan

Liu

2010

2010 20th International Conference on Pattern Recognition

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Hand pointing has been an intuitive gesture for human interaction with computers. Big challenges are still posted for accurate estimation of finger pointing direction in a 3D space. In this paper, we present a novel hand pointing estimation system based on two regular cameras, which includes hand region detection, hand finger estimation, two views' feature detection, and 3D pointing direction estimation. Based on the idea of binary pattern face detector [15], we extend the work to hand detection, in which a polar coordinate system is proposed to represent the hand region, and achieved a good result in terms of the robustness to hand orientation variation. To estimate the pointing direction, we applied an AAM based approach to detect and track 14 feature points along the hand contour from a top view and a side view. Combining two views of the hand features, the 3D pointing direction is estimated. The experiments have demonstrated the feasibility of the system.

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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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A computer vision system for on-screen item selection by finger pointing

Cited by 13 publications

References 12 publications

The 4D Touchpad: Unencumbered HCI With VICs

The 4D Touchpad: Unencumbered HCI With VICs

Hand Pointing Estimation for Human Computer Interaction Based on Two Orthogonal-Views

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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