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Automated Facial Feature Detection from Portrait and Range Images

Automated Facial Feature Detection from Portrait and Range I...

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IEEE Southwest Symposium on Image Analysis and Interpretation

作者： Sina Jahanbin Alan C. Bovik Hyohoon Choi Department of Electrical and Computer Engineering University of Texas Austin USA Computer Vision Research Laboratory Sealed Air Corporation San Jose USA

ISBN: (纸本)9781424422968;1424422965

We propose a novel technique to detect feature points from portrait and range representations of the face. In this technique, the appearance of each feature point is encoded using a set of Gabor wavelet responses extracted at multiple orientations and spatial frequencies. A vector of Gabor coefficients, called a jet, is computed at each pixel in the search window on a fiducial and compared with a set of jets, called a bunch, collected from a set of training data on the same type of fiducial. The desired feature point is located at the pixel whose jet is the most similar to the training bunch. This is the first time that Gabor wavelet responses were used to detect facial landmarks from range images. This method was tested on 1146 pairs of range and portrait images and high detection accuracies are achieved using a small number of training images. It is shown that co-localization using Gabor jets on range and portrait images resulted in better accuracy than using any single image modality. The obtained accuracies are competitive to that of other techniques in the literature.

关键词： Facial features Face detection computer vision Face recognition Shape Nose Active appearance model Data mining Robustness Detection algorithms

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Distributed Data Association and Filtering for Multiple Target Tracking

Distributed Data Association and Filtering for Multiple Targ...

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26th IEEE Conference on computer vision and Pattern Recognition (CVPR 2008), vol.6

作者： Ting Yu Ying Wu Nils O. Krahnstoever Peter H. Tu GE Global Research Visualization and Computer Vision Laboratory Niskayuna NY USA Department of Electrical Engineering and Computer Sciences Northwestern University Evanston IL USA

This paper presents a novel distributed framework for multi-target tracking with an efficient data association computation. A decentralized representation of trackers' motion and association variables is adopted. Considering the interleaved nature of data association and tracker filtering, the multi-target tracking is formulated as a missing data problem, and the solution is found by the proposed variational EM algorithm. We analytically show that 1) the posteriori distributions of trackers' motions (the real interests in terms of tracking applications) can be effectively computed in the E-step of the EM iterations, and 2) the solution of trackers' association variables can be pursued under a derived graph-based discrete optimization formulation, thus efficiently estimated in the M-step by the recently emerging graph optimization algorithms. The proposed approach is very general such that sophisticated data association priori and likelihood function can be easily incorporated. This general framework is tested with both simulation data and real world surveillance video. The reported qualitative and quantitative studies verify the effectiveness and low computational cost of the algorithm.

关键词： Target tracking Distributed computing Filtering algorithms Algorithm design and analysis Motion analysis Motion estimation Testing Computational modeling Surveillance Computational efficiency

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A preliminary study on the accuracy of wireless sensor fusion for biomotion capture

A preliminary study on the accuracy of wireless sensor fusio...

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5th International Workshop on Wearable and Implantable Body Sensor Networks, BSN 2008, in conjunction with the 5th International Summer School and Symposium on Medical Devices and Biosensors, ISSS-MDBS 2008

作者： Kwang, Yong Lim Dong, Wei Goh, Francis Young Koon Kim, Doang Nguyen Chen, I.-Ming Song, Huat Yeo Duh, Henry Been Lirn Robotics Research Centre School of Mechanical and Aerospace Engineering Nanyang Technological University 50 Nanyang Avenue Singapore 639798 Singapore Interactive and Digital Media Institute Department of Electrical and Computer Engineering National University of Singapore 4 Engineering Drive 3 Singapore 117576 Singapore

ISBN: (纸本)9781424422531

A 2.4GHz low-power wireless platform based on the Texas Instruments CC2431 System-On-Chip (SOC) transceiver is used to conduct a preliminary investigation of the accuracy of a 3-axis accelerometer fused with a linear encoder for capturing high-speed motion. Calibration of the fused sensors is accomplished by extracting the gravity related term from the accelerometer when it is under static conditions. When moving at acceleration greater than 1.1g, the wireless platform switches to the linear encoder for local joint angle data. To ascertain the concept of sensor calibration when the sensor is under static conditions, experiments that compare results from a high-speed motion analysis system (Silicon Coach) and the combination of the accelerometer and linear encoder is carried out. Experimental results for pronation and supination of the forearm that has acceleration less than 1.1g show that the accelerometer and linear encoder produces a low root mean square (RMS) error of 5.3 and 6.6 respectively. Correlation coefficient for the accelerometer and linear encoder for the above experiment are 98.7% and 98.9% respectively. A similar experiment where the maximum acceleration exceeds 1.1g produces a RMS error of 10.5 and 6.9 for the accelerometer and linear encoder respectively. Correlation coefficients for both sensors are approximately 98.2%. This study shows that linear encoder as a joint angle measurement device is preferred for both high and low acceleration motion while the errors associated with extracting gravity related tilt from the accelerometer increases with increasing acceleration. ©2008 IEEE.

关键词： Accelerometers

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Fuzzy Vergence Control for an Active Binocular vision System

Fuzzy Vergence Control for an Active Binocular Vision System

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IEEE International Conference on Cybernetic Intelligent Systems

作者： Nikolaos Kyriakoulis Antonios Gasteratos Spyridon G. Mouroutsos Laboratory of Robotics and Automation Department of Production and Management Engineering School of Engineering Democritus University of Thrace Laboratory of Special Engineering Department of Electrical and Computer Engineering School of Engineering Democritus University of Thrace

ISBN: (纸本)9781424429141

Vergence control in binocular vision systems involves the adjustment of the angle between the two cameras' axes so that they are both fixated at the same point of interest. Vergence enables stereo vision systems to perceive depth and to acquire obstacle maps. Vergence movement is directly related to the binocular fusion. Additionally, the decision for convergence or divergence is extracted either by motion affine models or by mathematical ones. In this paper, a new method for extracting the cameras' movement direction, for verge or diverge, is presented. The movement decision is performed by a fuzzy control system, the inputs of which are the zero-mean normalized cross correlation (ZNCC) and the depth estimations at each time step. The suggested system can be used in any active binocular system and is computationally inexpensive. Moreover, the proposed system is independent to a priori camera calibration.

关键词： Vergence angle Zero mean normalized cross correlation Fuzzy logic binocular convergence Fuzzy logic computer vision Binocular vision fuzzy control systems new methods camera calibration Diverge BINOCULARS Cameras

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Automated facial feature detection and face recognition using Gabor features on range and portrait images

Automated facial feature detection and face recognition usin...

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IEEE International Conference on Image Processing

作者： Sina Jahanbin Hyohoon Choi Rana Jahanbin Alan C. Bovik Department of Electrical and Computer Engineering University of Texas Austin Austin TX USA Computer Vision Research Laboratory Sealed Air Corporation San Jose CA USA Department of Biomedical Engineering University of Texas Austin Austin TX USA

In this paper, we present a novel identity verification system based on Gabor features extracted from range (3D) representations of faces. Multiple landmarks (fiducials) on a face are automatically detected using these Gabor features. Once the landmarks are identified, the Gabor features on all fiducials of a face are concatenated to form a feature vector for that particular face. Linear discriminant analysis (LDA) is used to reduce the dimensionality of the feature vector while maximizing the discrimination power. These novel features were tested on 1196 range images. The same features were also extracted from portrait images, and the accuracies of both modalities were compared. A superior verification accuracy was obtained using the range data, and a highly competitive accuracy to that of other techniques in the literature was also obtained for the portrait data.

关键词： Facial features Face detection Face recognition Biometrics Fingerprint recognition Iris Feature extraction Vectors Linear discriminant analysis Testing

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Development of a stereo vision system for remotely operated robots: A control and video streaming architecture

Development of a stereo vision system for remotely operated ...

引用

IEEE International Symposium on Virtual Environments, Human-computer Interfaces and Measurement Systems (VECIMS)

作者： A. Amanatiadis A. Gasteratos C. Georgoulas L. Kotoulas I. Andreadis Laboratory of Electronics Department of Electrical and Computer Engineering Democritus University of Thrace Xanthi Greece Laboratory of Robotics and Automation Department of Production and Management Engineering Democritus University of Thrace Xanthi Greece

This paper describes the open and flexible architecture of a stereo vision system prototype, using open source software. The system is designed for teleoperated robots and includes a four degrees of freedom stereo head mechanism, a pair of high performance digital cameras, a head tracker and a head mounted display. All processes for the head control and video streaming are performed in Linux-based Real-time Operating Systems using open source libraries under GPL license. Experimental results showed that our system is capable of satisfying the hard-real time requirements for the head control, with great precision, and a low latency for the stereo video streaming. The video streaming management is particularly sophisticated resulting in a flexible, efficient and reliable service.

关键词： Streaming media Robots computers Kernel Cameras Real time systems Stereo vision

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Camera Handoff with Adaptive Resource Management for Multi-camera Multi-target Surveillance

Camera Handoff with Adaptive Resource Management for Multi-c...

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IEEE Conference on Advanced Video and Signal Based Surveillance (AVSS)

作者： Chung-Hao Chen Yi Yao David Page Besma Abidi Andreas Koschan Mongi Abidi Imaging Robotics and Intelligent Systems Laboratory Department of Electrical Engineering and Computer Science University of Tennessee Knoxville TN USA GE Global Research Center Niskayuna NY USA

Camera handoff is a crucial step to generate a continuously tracked and consistently labeled trajectory of the object of interest in multi-camera surveillance systems. Most existing camera handoff algorithms concentrate on data association, namely consistent labeling, where images of the same object are matched across different cameras. However, most real-time object tracking systems see a decrease in the system's frame rate as the number of tracked objects increases. To address this issue, we propose to incorporate an adaptive resource management mechanism into camera handoff. In so doing, cameras¿ resources can be dynamically allocated to multiple objects according to their priorities and hence the required minimum frame rate can be maintained. Experimental results illustrate that the proposed camera handoff algorithm is capable of maintaining a constant frame rate and of achieving a substantially improved handoff success rate by approximately 20% in comparison with the algorithm presented by Khan and Shah.

关键词： Resource management Surveillance Labeling Real time systems Intelligent robots USA Councils Videoconference Robot vision systems Smart cameras Robot kinematics

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Integrated planning and image-guided control for planar needle steering

Integrated planning and image-guided control for planar need...

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IEEE/RAS-EMBS International Conference on Biomedical robotics and Biomechatronics (BioRob)

作者： Kyle B. Reed Vinutha Kallem Ron Alterovitz Ken Goldbergxz Allison M. Okamura Noah J. Cowan Department of Mechanical Engineering Laboratory for Computational Sensing and Robotics Johns Hopkins University Baltimore USA Department of Electrical Engineering and Computer Sciences UCSF Comprehensive Cancer Center Department of Industrial Engineering and Operations Research University of California Berkeley USA

Flexible, tip-steerable needles promise to enhance physicianspsila abilities to accurately reach targets and maneuver inside the human body while minimizing patient trauma. Here, we present a functional needle steering system that integrates two components: (1) a patient-specific 2D pre- and intraoperative planner that finds an achievable route to a target within a planar slice of tissue (Stochastic Motion Roadmap), and (2) a low-level image-guided feedback controller that keeps the needle tip within that slice. The planner generates a sequence of circular arcs that can be realized by interleaving pure insertions with 180deg rotations of the needle shaft. This pre-planned sequence is updated in realtime at regular intervals. Concurrently, the low-level image-based controller servos the needle to remain close to the desired plane between plan updates. Both planner and controller are predicated on a previously developed kinematic nonholonomic model of beveltip needle steering. We use slighly different needles here that have a small bend near the tip, so we extend the model to account for discontinuities of the tip position caused by 180deg rotations. Further, during large rotations of the needle base, we maintain the desired tip angle by compensating for torsional compliance in the needle shaft, neglected in previous needle steering work. By integrating planning, control, and torsion compensation, we demonstrate both accurate targeting and obstacle avoidance.

关键词： Needles Shafts USA Councils Automatic control Medical control systems Control systems Robot sensing systems Physics computing Biological tissues Biomechatronics

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A systematic topological method for fingerprint singular point detection

A systematic topological method for fingerprint singular poi...

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International Conference on Control, Automation, robotics and vision (ICARCV)

作者： H.K. Lam Z. Hou W.Y. Yau T.P. Chen J. Li Computer Vision and Image Understanding Department Institute for Infocomm Research-Agency for Science Technology and Research Singapore School of Electrical and Electronic Engineering Nanyang Technological University Singapore

Singular point detection is an important issue in fingerprint image analysis. General methods like Poincare index method can detect singular points in non-arch type fingerprints but fail on arch-type fingerprints. Some more sophisticated methods like complex filter method also face the same problem. In this paper, we propose a systematic method for detecting singular points in fingerprint images which utilizes the most fundamental topological feature of acquired fingerprints as the basis for singular point identification. The method differentiates the input fingerprint between arch type and non-arch type. For non-arch type fingerprints singular points are detected as intersection points in a c(>2) level segmentation map. As for arch type fingerprints, singular points are identified from the symmetric line of the fingerprint structure. The method is evaluated using the NIST DB4 database and compared with the complex filter method. The proposed method attains near 90% success rate in detecting singular points and the displacement from ground truth is comparable to that of the complex filter method. Moreover our method is more than once faster in CPU time.

关键词： Fingerprint recognition Image matching Filters robotics and automation computer vision Image segmentation Automatic control Robot control Control systems Robot vision systems

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Multi-modal Task Apportionment in dynamic multi-factor systems

Multi-modal Task Apportionment in dynamic multi-factor syste...

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Chinese Control and Decision Conference, CCDC

作者： Hooman A. Samani C. Fua T. Chai S. S. Ge C. C. Hang Social Robotics Laboratory Interactive Digital Media Institute Department of Electrical and Computer Engineering National University of Singapore Singapore Key Laboratory of Process Industry Automation Ministry of Education and Research Center of Automation Northeastern University China

The problem of task apportionment for dynamic multi-factor systems is categorized in three different scenarios in this paper: admin, crew and factor based. The system is discussed based on the realistic manufacturing environments as an application platform in order to consider the robust Task Apportionment system for such a case but the proposed system can be generalized to any similar system. Both centralized and decentralized systems are considered and task allocation, re-allocation, exchange and execution as layers of task apportionment methods are designed and described in each system. The system may switch between modes according the feedback information of communication capabilities or uses different modes for each part of the platform.

关键词： Switches Resource management Manufacturing systems Manufacturing Dynamic scheduling Servers Robustness

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