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IEEE computer Society Conference on computer Vision and Pattern Recognition Workshops (CVPRW)

作者： Jingu Heo S.G. Kong B.R. Abidi M.A. Abidi Imaging Robotics and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Tennessee Knoxville TN USA

This paper describes a fusion of visual and thermal infrared (IR) images for robust face recognition. Two types of fusion methods are discussed: data fusion and decision fusion. Data fusion produces an illumination-invariant face image by adaptively integrating registered visual and thermal face images. Decision fusion combines matching scores of individual face recognition modules. In the data fusion process, eyeglasses, which block thermal energy, are detected from thermal images and replaced with an eye template. Three fusion-based face recognition techniques are implemented and tested: Data fusion of visual and thermal images (Df), Decision fusion with highest matching score (Fh), and Decision fusion with average matching score (Fa). A commercial face recognition software FaceIt® is used as an individual recognition module. Comparison results show that fusion-based face recognition techniques outperformed individual visual and thermal face recognizers under illumination variations and facial expressions.

关键词： Robustness Face recognition Face detection Lighting Optical imaging intelligent robots Infrared imaging Pattern recognition computer vision Temperature

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Fusion of visual, thermal, and range as a solution to illumination and pose restrictions in face recognition

Fusion of visual, thermal, and range as a solution to illumi...

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International Carnahan Conference on Security Technology

作者： B. Abidi S. Huq M. Abidi Imaging Robotics and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Tennessee Knoxville TN USA

This paper summarizes the various components of face recognition research conducted at the IRIS Lab. First, fusion of visual and thermal infrared (IR) images for robust face recognition is discussed. Two techniques are implemented: data fusion and decision fusion. With the knowledge that eyeglasses block the emission of thermal energy, an algorithm is designed to detect and replace eyeglasses with an eye template in thermal images. A commercial face recognition software (FaceIt/spl reg/) is used in the evaluation of the various fusion algorithms. Comparison results show that fusion-based face recognition outperforms individual visual or thermal face recognizers under illumination variations and facial expressions. Efforts in the 3D arena are also described. Results of high resolution stereo-based 3D reconstruction of faces are shown and analyzed, in a first approach, then in a second approach, a warping technique is applied to overlay color and thermal textures on 3D mannequin head models, obtained using a laser range scanner.

关键词： Lighting Face recognition Face detection Iris Infrared imaging Robustness Algorithm design and analysis Software algorithms Image reconstruction Image color analysis

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Localization of simultaneous moving sound sources for mobile robot using a frequency- domain steered beamformer approach

Localization of simultaneous moving sound sources for mobile...

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IEEE International Conference on robotics and Automation (ICRA)

作者： J.-M. Valin F. Michaud B. Hadjou J. Rouat LABORIUS-Research Laboratory on Mobile Robotics and Intelligent Systems Department of Electrical Engineering and Computer Engineering Université de Sherbrook Sherbrooke QUE Canada

Mobile robots in real-life settings would benefit from being able to localize sound sources. Such a capability can nicely complement vision to help localize a person or an interesting event in the environment, and also to provide enhanced processing for other capabilities such as speech recognition. We present a robust sound source localization method in three-dimensional space using an array of 8 microphones. The method is based on a frequency-domain implementation of a steered beamformer along with a probabilistic post-processor. Results show that a mobile robot can localize in real time multiple moving sources of different types over a range of 5 meters with a response time of 200 ms.

关键词： Mobile robots Auditory system Orbital robotics intelligent robots Head Acoustic noise Humans Robustness Microphone arrays Signal processing

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Enhanced robot audition based on microphone array source separation with post-filter

Enhanced robot audition based on microphone array source sep...

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IEEE International Workshop on intelligent Robots and systems (IROS)

作者： J.-M. Valin J. Rouat F. Michaud Department of Electrical Engineering and Computer Engineering LABORIUS-Research Laboratory on Mobile Robotics and Intelligent Systems Université de Sherbrook Sherbrooke QUE Canada

We propose a system that gives a mobile robot the ability to separate simultaneous sound sources. A microphone array is used along with a real-time dedicated implementation of geometric source separation and a post-filter that gives us a further reduction of interferences from other sources. We present results and comparisons for separation of multiple non-stationary speech sources combined with noise sources. The main advantage of our approach for mobile robots resides in the fact that both the frequency domain geometric source separation algorithm and the post-filter are able to adapt rapidly to new sources and non-stationarity. Separation results are presented for three simultaneous interfering speakers in the presence of noise. A reduction of log spectral distortion (LSD) and increase of signal-to-noise ratio (SNR) of approximately 10 dB and 14 dB are observed.

关键词： Microphone arrays Source separation Mobile robots Acoustic noise Auditory system Humans intelligent robots Interference Robot sensing systems Mobile computing

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Modular hybrid Petri nets for studying multi-operational production systems where parts follow multiple alternative processes

Modular hybrid Petri nets for studying multi-operational pro...

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IEEE International Conference on robotics and Automation (ICRA)

作者： G.J. Tsinarakis K.P. Valavanis Intelligent Systems and Robotics Laboratory Department of Production Engineering and Management Technical University of Crete Chania Greece Department of Computer Science and Engineering University of South Florida Center for Robot-Assisted Search and Rescue Tampa FL USA

This work presents a modular hybrid timed Petri net (MHTPN) methodology used to study multi-operational production systems in which parts are used for the production of different product types. This research generalizes work presented in Tsinarakis, GJ et al., (2003) that studied production systems where all parts of the same type were used for the production of a type of final products following a common route. 3 fundamental system modules are derived; their MHTPN models are defined, followed by modules synthesis to obtain the overall system Petri net. For any topology, system's nodes and invariants are calculated. Applicability of the method is illustrated through an analytical example.

关键词： Petri nets Production systems Topology Fluid dynamics Assembly intelligent robots Hybrid intelligent systems Laboratories Production engineering engineering management

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Using a non-prior training active feature model

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2004年 3333卷 69-78页

作者： Kim, Sangjin Kang, Jinyoung Shin, Jeongho Lee, Seongwon Paik, Joonki Kang, Sangkyu Abidi, Besma Abidi, Mongi Department of Image Engineering Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University 221 Huksuk-Dong Tongjak-Ku Seoul 156-756 Korea Republic of Imaging Robotics and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Tennessee Knoxville TN 27996-2100 United States

This paper presents a feature point tracking algorithm using optical flow under the non-prior training active feature model (NPT-AFM) framework. The proposed algorithm mainly focuses on analysis of deformable objects, and provides real-time, robust tracking. The proposed object tracking procedure can be divided into two steps: (i) optical flow-based tracking of feature points and (ii) NPT-AFM for robust tracking. In order to handle occlusion problems in object tracking, feature points inside an object are estimated instead of its shape boundary of the conventional active contour model (ACM) or active shape model (ASM), and are updated as an element of the training set for the AFM. The proposed NPT-AFM framework enables the tracking of occluded objects in complicated background. Experimental results show that the proposed NPT-AFM-based algorithm can track deformable objects in real-time. © Springer-Verlag 2004.

关键词： Optical flows

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Textual message read by a mobile robot

Textual message read by a mobile robot

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IEEE International Workshop on intelligent Robots and systems (IROS)

作者： D. Letourneau F. Michaud J.-M. Valin C. Proulx Department of Electrical Engineering and Computer Engineering Universite de Sherbrooke LABORIUS - Research Laboratory on Mobile Robotics and Intelligent Systems Sherbrooke Quebec CANADA

Giving the ability to read characters and symbols is highly desirable for increased autonomy of mobile robots operating in the real world. The idea is fairly simple: give a robot the ability to acquire an image of a message to read, extract the symbols and recognize them. Image character recognition research has been going on for decades now, with good results. But compared to conventional character recognition systems, the challenge with a mobile robot is to find a textual message to capture in the world and to get a good view of the message, knowing that the viewpoint of the robot depends on its position in relation to the message, which cannot be pre-specified. In this paper we present our approach making it possible for an autonomous mobile robot to read messages. We outline the constraints under which the approach works, and present results obtained using a Pioneer 2 robot equipped with a Pentium 233 MHz and a pan-tilt-zoom camera.

关键词： Mobile robots Robot vision systems Cameras intelligent robots Character recognition Image recognition Navigation Laboratories Mobile computing intelligent systems

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Automatic face region tracking for highly accurate face recognition in unconstrained environments

Automatic face region tracking for highly accurate face reco...

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

作者： Y.-O. Kim J. Paik Jingu Heo A. Koschan B. Abidi M. Abidi Korea Electronics and Technology Institute Puchon Gyeonggi South Korea Image Processing Laboratory Department of Image Engineering Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul South Korea Imaging Robotics and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Tennessee Knoxville USA

We present a combined real-time face region tracking and highly accurate face recognition technique for an intelligent surveillance system. High-resolution face images are very important to achieving accurate identification of a human face. Conventional surveillance or security systems, however, usually provide poor image quality because they use only fixed cameras to record scenes passively. We have implemented a real-time surveillance system that tracks a moving face using four pan-tilt-zoom (PTZ) cameras. While tracking, the region-of-interest (ROI) can be obtained by using a low-pass filter and background subtraction with the PTZ. Color information in the ROI is updated to extract features for optimal tracking and zooming. FaceIt/sup /spl reg//, which is one of the most popular face recognition software packages, is evaluated and then used to recognize the faces from the video signal. Experimentation with real human faces showed highly acceptable results in the sense of both accuracy and computational efficiency.

关键词： Face recognition Surveillance Real time systems Humans Cameras intelligent systems Security Image quality Layout Low pass filters

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Image Processing-Based Mine Detection Techniques: A Review

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Subsurface Sensing Technologies and Applications 2002年第3期3卷 153-202页

作者： Paik, Joonki Lee, Cheolha P. Abidi, Mongi A. Imaging Robotics and Intelligent Systems Laboratory Department of Electrical and Computer Engineering The University of Tennessee Knoxville

Various mine detection techniques are reviewed with particular emphasis on signal and image processing methods. Based on the target, mines are classified into two types; anti-tank mine (ATM) and anti-personnel mine (APM). Because of the variety of mine types, current mine detection techniques are diversified. The assumption is made that most mine detection techniques consist of sensor, signal processing, and decision processes. For the sensor part, ground penetration radar (GPR), infrared (IR), and ultrasound (US) sensors are reviewed and their characteristics are summarized for the corresponding output signals. For the signal processing and decision parts, a set of image processing techniques including filtering, enhancement, feature extraction, and segmentation are surveyed. Segmentation is used to extract mine signal from various competing signals. For most image processing techniques covered by this paper, mine detection related experimental results are included or reproduced from existing works.

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Triangle mesh-based edge detection and its application to surface segmentation and adaptive surface smoothing

Triangle mesh-based edge detection and its application to su...

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IEEE International Conference on Image Processing

作者： Y. Sun D.L. Page J.K. Paik A. Koschan M.A. Abidi Imaging Robotics and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Tennessee Knoxville USA

Triangle meshes are widely used in representing surfaces in computer vision and computer graphics. Although 2D image processing-based edge detection techniques have been popular in many application areas, they are not well developed for surfaces represented by triangle meshes. This paper proposes a robust edge detection algorithm for triangle meshes and its applications to surface segmentation and adaptive surface smoothing. The proposed edge detection technique is based on eigen analysis of the surface normal vector field in a geodesic window. To compute the edge strength of a certain vertex, the neighboring vertices in a specified geodesic distance are involved. Edge information are used further to segment the surfaces with the watershed algorithm and to achieve edge-preserved, adaptive surface smoothing. The proposed algorithm is novel in robustly detecting edges on triangle meshes against noise. The 3D watershed algorithm is an extension from previous work. Experimental results on surfaces reconstructed from multi-view real range images are presented.

关键词： Image edge detection Smoothing methods Application software Image segmentation Surface reconstruction computer vision computer graphics Geophysics computing Noise robustness Image reconstruction

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