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Communication via eye blinks and eyebrow raises: Video-based human-computer interfaces

Universal Access in the Information Society 2003年第4期2卷 359-373页

作者： Grauman, K. Betke, M. Lombardi, J. Gips, J. Bradski, G.R. Vision Interface Group AI Laboratory Massachusetts Institute of Technology 77 Massachusetts Avenue CambridgeMA02139 United States Computer Science Department Boston University 111 Cummington St BostonMA02215 United States EagleEyes Computer Science Department Boston College Fulton Hall Chestnut HillMA02467 United States Vision Graphics and Pattern Recognition Microcomputer Research Laboratory Intel Corporation SC12-303 2200 Mission College Blvd Santa ClaraCA95054-1537 United States

Two video-based human-computer interaction tools are introduced that can activate a binary switch and issue a selection command. "BlinkLink," as the first tool is called, automatically detects a user's eye blinks and accurately measures their durations. The system is intended to provide an alternate input modality to allow people with severe disabilities to access a computer. Voluntary long blinks trigger mouse clicks, while involuntary short blinks are ignored. The system enables communication using "blink patterns:" sequences of long and short blinks which are interpreted as semiotic messages. The second tool, "EyebrowClicker," automatically detects when a user raises his or her eyebrows and then triggers a mouse click. Both systems can initialize themselves, track the eyes at frame rate, and recover in the event of errors. No special lighting is required. The systems have been tested with interactive games and a spelling program. Results demonstrate overall detection accuracy of 95.6% for BlinkLink and 89.0% for EyebrowClicker. © Springer-Verlag 2003.

关键词： Computer vision

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A new correspondenceless geometric algorithm for automatic inspection of filter components

A new correspondenceless geometric algorithm for automatic i...

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IEEE International Conference on Industrial Technology (ICIT)

作者： M.A. Rodrigues Yonghuai Liu AI and Pattern Recognition Research Group Department of Computer Science University of Hull Hull UK

We report on the design and validation of a method for correspondenceless estimation of transformation parameters. The problem we are tackling is connected with the verification of dimensional specifications of filter components in a manufacturing line. Our proposed method consists of acquiring range images of the same object's region from known, different viewpoints and use this information to calibrate camera parameters. Calibration errors can then be used to reason about actual physical dimensions and compare these with given specifications. We are investigating a correspondenceless method because the establishment of point to point correspondences between real images is a truly challenging task. Our proposed algorithm is based on geometric properties of image points which can be defined as invariants uniquely determined by the specific rigid transformation. The same invariants are also defined for a small subset of data, providing that the subset contains at least three data points. The algorithm is based on computing two sets of possible transformation parameters using different subsets of image data. The algorithm makes full use of rigid geometric constraints of image points synthesised into a single coordinate system and provides a closed form solution to all parameters of interest. We also implemented another well known correspondenceless calibration algorithm based on the scatter matrix. Experimental results have shown that the proposed algorithm is generally more accurate than the scatter matrix based algorithm and that it can be effectively used in the context of the described industrial inspection task.

关键词： Inspection Filters air cleaners Calibration Electrical equipment industry Manufacturing industries Parameter estimation Cameras Scattering Algorithm design and analysis

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Using rigid constraints to analyse motion parameters from two sets of 3D corresponding point pattern 8th

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8th International Conference on Computer Analysis of Images and patterns, CaiP 1999

作者： Liu, Yonghuai Rodrigues, Marcos A. AI and Pattern Recognition Research Group Department of Computer Science The University of Hull HullHU6 7RX United Kingdom

ISBN: (纸本)3540663665

Given a rigid body motion expressed by a set of 2D or 3D correspondences, the distance between feature points and angular information can be used as rigid constraints to calibrate motion parameters. In this paper, we first present a novel geometrical analysis of proper- ties of reflected correspondence vectors. The analysis provides explicit expressions for distance between feature points and angle measurement synthesised into a single coordinate frame providing the closed form solutions to all motion parameters of interest. A novel calibration algorithm is proposed and compared with an algorithm based on the least squares method. The algorithm demonstrates the importance of the geometrical properties of reflected correspondence vectors to motion parameter estimation and that it is generally more accurate than algorithms based on the least squares method. © Springer-Verlag Berlin Heidelberg 1999.

关键词： Parameter estimation

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A two-stage approach to 3D scene structural analysis from a single two-dimensional image 3

A two-stage approach to 3D scene structural analysis from a ...

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3rd International Conference on Computational Intelligence and Multimedia Applications, ICCIMA 1999

作者： Liu, Y. Rodrigues, M.A. AI and Pattern Recognition Research Group Department of Computer Science Hull University HullHU6 7RX United Kingdom

ISBN: (纸本)0769503004

Structural analysis of a 3D scene from 2D image pixel positions is an important and unresolved issue in image processing and pattern recognition. Current algorithms for 3D structural analysis do not explicitly use geometrical properties of distance between feature points and angle information as constraints to calibrate transformation parameters. We propose a novel two-stage approach to analyse the structure of a 3D scene based on the explicit expressions of distance and angle measurement. In the first stage, we transform the 3D-2D problem into a linear problem and propose a robust algorithm based on the total least squares method to estimate the rotation matrix and translation vector. In the second stage, we propose a coarse-to-fine geometric algorithm to refine the estimation. The proposed two-stage approach provides the closed form solutions to structural parameters through the analysis of image correspondence vectors synthesised into a single coordinate frame. For a comparative study of performance, we also extended a well known 2D-2D epipolar geometry algorithm proposed by R.Y. Tsai and T.S. Huang (1984) to solve 3D-2D problems. Experimental results show that the proposed approach and geometric algorithms are in general more accurate, stable, and efficient than the extended Tsai and Xuang algorithm. © 1999 IEEE.

关键词： Structural analysis

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A new correspondenceless geometric algorithm for motion estimation from range images 3

A new correspondenceless geometric algorithm for motion esti...

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3rd IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 1999

作者： Liu, Yonghuai Rodrigues, Marcos A. AI and Pattern Recognition Research Group Department of Computer Science The University of Hull HullHU6 7RX United Kingdom

ISBN: (纸本)0780358066

A number of techniques for motion estimation from range images have been proposed over the past decade. Based on a number of estimation constraints, varying degrees of accuracy and robustness have been achieved. A feature of existing techniques is that they do not explicitly use distance and angle information as rigid constraints to estimation. We have investigated the implications of this to the performance of algorithms and, in this paper, we propose a new correspondenceless algorithm for motion estimation from range images making full use of rigid constraints and projection information. The algorithm provides a closed form solution to all parameters of interest based on geometrical properties of correspondence vectors that have been synthesised into a single coordinate frame. For a comparative study of performance, we also implemented another correspondenceless motion estimation algorithm based on the eigenstructure analysis of the scatter matrix. Experimental results based on both synthetic and real images show that the proposed algorithm is accurate and robust and that it compares favourably with the scatter matrix algorithm. © 1999 IEEE.

关键词： Motion estimation

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A new robust geometrical algorithm for motion estimation from range images

A new robust geometrical algorithm for motion estimation fro...

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1999 International Conference on Information Intelligence and Systems, ICIIS 1999

作者： Liu, Yonghuai Rodrigues, Marcos A. AI and Pattern Recognition Research Group Department of Computer Science University of Hull HullHU6 7RX United Kingdom

ISBN: (纸本)0769504469

In this paper, we present a geometric analysis of reflected correspondence vectors synthesised into a single coordinate frame. The analysis provides an extension to Chasles' work for machine vision tasks (R.S. Ball, 1900), by providing an explicit representation of motion parameters based on the use of distance between feature points and angle information and also by providing a clear insight into the number of solutions to motion parameters. We demonstrate that robust motion estimation algorithms can be developed from the analysis by proposing and implementing a calibration algorithm making full use of the geometric properties of reflected correspondence vectors. A fuzzy reasoning step has been included in the algorithm in order to counteract the adverse effects of noise and outliers. Accuracy and robustness are assessed and compared with a constraint least squares algorithm using both synthetic and real range image data. © 1999 IEEE.

关键词： Motion estimation

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A new robust geometrical algorithm for motion estimation from range images

A new robust geometrical algorithm for motion estimation fro...

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International Conference on Information Intelligence and Systems

作者： Yonghuai Liu M.A. Rodrigues Department of Computer Science AI and Pattern Recognition Research Group University of Hull Hull UK

We present a geometric analysis of reflected correspondence vectors synthesised into a single coordinate frame. The analysis provides an extension to Chasles' work for machine vision tasks (R.S. Ball, 1900), by providing an explicit representation of motion parameters based on the use of distance between feature points and angle information and also by providing a clear insight into the number of solutions to motion parameters. We demonstrate that robust motion estimation algorithms can be developed from the analysis by proposing and implementing a calibration algorithm making full use of the geometric properties of reflected correspondence vectors. A fuzzy reasoning step has been included in the algorithm in order to counteract the adverse effects of noise and outliers. Accuracy and robustness are assessed and compared with a constraint least squares algorithm using both synthetic and real range image data.

关键词： Robustness Motion estimation Least squares methods Motion analysis Image analysis Machine vision Algorithm design and analysis Calibration Robot vision systems Parameter estimation

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Rigidity analysis from range image data for automatic inspection of filter components

Rigidity analysis from range image data for automatic inspec...

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： M.A. Rodrigues Y. Liu AI and Pattern Recognition Research Group Department of Computer Science University of Hull Hull UK

Recent developments in computer vision and pattern recognition have enabled the development of sophisticated vision-based quality control systems for automatic inspection. We present a new geometrical analysis of rigid body transformation parameters from properties of reflected correspondence vectors. Based on this analysis, we propose a novel algorithm to calibrate transformation parameters of 3D objects in a fast production line of filter components. The algorithm performs a rigidity analysis from range images acquired from two cameras, making full use of distance and angle information providing a closed form solution to all parameters of interest. The method is used in conjunction with a decision support system where components falling outside specified thresholds are to be rejected. For a comparative study of algorithm performance, we also implemented a well known procedure for rigidity analysis based on quaternions. Experimental results demonstrate that our novel algorithm has a number of advantages over the quaternion method and that its performance is superior or similar to the quaternion method.

关键词： Image analysis Inspection Algorithm design and analysis Quaternions Performance analysis Computer vision pattern recognition Quality control Production Filters

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Geometrical analysis of two sets of 3D correspondence data patterns

Geometrical analysis of two sets of 3D correspondence data p...

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International Conference on Shape Modeling and Applications

作者： M.A. Rodrigues Yonghuai Liu AI and Pattern Recognition Research Group Department of Computer Science University of Hull Hull UK

Given two sets of image correspondence data, the analysis of the corresponding rigid body transformation that accurately describes the object's motion in 3D space is a fundamental problem in image understanding. While many methods have been put forward to analyse 3D transformations, such methods do not make use of the vector distance between feature points and angular information as constraints to analyse transformation parameters. Current methods and algorithms have also suffered from the problems of lack of efficiency, sensitivity to noise, and multiplicity of solutions. In this paper we present a novel geometrical analysis of rigid body transformations and a novel algorithm to calibrate transformation parameters based on image correspondence. The algorithm is validated through experimental calibration and a comparison is made with calibration implemented by the least squares method. We demonstrate that the proposed algorithm works well in the presence of noise and that its performance is in general superior to algorithms based on the least squares method.

关键词： pattern analysis Calibration Least squares methods Image analysis Information analysis Machine vision Coordinate measuring machines Shape Inspection Artificial intelligence

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A new correspondenceless geometric algorithm for motion estimation from range images

A new correspondenceless geometric algorithm for motion esti...

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IEEE International Symposium on Computational Intelligence in Robotics and Automation (CIRA)

作者： Yonghuai Liu M.A. Rodrigues AI and Pattern Recognition Research Group Department of Computer Science University of Hull Hull UK

A number of techniques for motion estimation from range images have been proposed over the past decade. A feature of existing techniques is that they do not explicitly use distance and angle information as rigid constraints to estimation. We have investigated the implications of this to the performance of algorithms and, in this paper, we propose a new correspondenceless algorithm for motion estimation from range images making full use of rigid constraints and projection information. The algorithm provides a closed form solution to all parameters of interest based on geometrical properties of correspondence vectors that have been synthesised into a single coordinate frame. For a comparative study of performance, we also implemented another correspondenceless motion estimation algorithm based on the eigenstructure analysis of the scatter matrix. Experimental results based on both synthetic and real images show that the proposed algorithm is accurate and robust and that it compares favourably with the scatter matrix algorithm.

关键词： Motion estimation Calibration air cleaners Robustness Filters Cameras Scattering Quaternions Artificial intelligence pattern recognition

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