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Dynamic Weighting of Facial Features for Automatic Pose-Invariant Face Recognition

Dynamic Weighting of Facial Features for Automatic Pose-Inva...

引用

Canadian Conference on computer and Robot vision, CRV

作者： Eslam A. Mostafa Aly A. Farag Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA

This paper proposes an automatic pose-invariant face recognition system. In our approach, we consider the texture information around the facial features to compute the similarity measure between the probe and gallery images. The weight of each facial feature is dynamically estimated based on its robustness to the pose of the captured image. An approach to extract the 9 facial features used to initialize the Active shape model is proposed. The approach is not dependent on the texture around the facial feature only but incorporates the information obtained about the facial feature relations. Our face recognition system is tested on common datasets in pose evaluation CMU-PIE and FERET. The results show out-performance of the state of the art automatic face recognition systems.

关键词： Facial features Face Shape Face recognition Feature extraction Detectors Active appearance model

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Computationally light forehead segmentation from thermal images

Computationally light forehead segmentation from thermal ima...

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IEEE International Conference on image processing

作者： Travis R. Gault Aly A. Farag Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA

Thermal images are often paired with visible spectrum images captured simultaneously-as surface features are easier to identify with proper illumination-to determine the thermal feature locations. Not all thermal images are necessarily recorded this way, yet determining salient feature regions is beneficial to other tasks. The forehead region is useful to the field of vital signs analysis and the goal of this work is automatically identifying the forehead region solely from thermal images. The anatomy of the forehead and its thermo-dynamic properties lend itself to minimizing the variance of a facial thermogram. Experiments conducted indoors on 32 subjects under normal, exercise and pain conditions. The proposed solution identifies the forehead region with 90-95% accuracy in 80ms or less, without initialization or training data, and can be easily implemented in parallel.

关键词： Forehead Skin Hair image segmentation Imaging Blood Heating

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A Passive Stereo System for 3D Human Face Reconstruction and Recognition at a Distance

A Passive Stereo System for 3D Human Face Reconstruction and...

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IEEE computer Society Conference on computer vision and Pattern Recognition Workshops

作者： Mostafa Abdelrahman Asem Ali Shireen Elhabian Ham Rara Aly A. Farag Computer Vision and Image Processing Laboratory (CVIP) University of Louisville Louisville KY 40292

ISBN: (纸本)9781467316118

In this paper, we propose a front-end framework for 3D human face reconstruction and recognition at a distance. A stereo acquisition system is built and deployed to capture stereo pairs of subjects at different distances. Three main issues are addressed to achieve accurate face reconstruc- tion, which leads to good recognition;Different illumina- tion conditions between the stereo pair due to larger base- line and further distances, where a fast similarity measure based on normalized cross correlation is shown to tackle such problem. Due to the non-convexity nature of a human face, concave regions introduce occluded regions where cu- bic Splines are used to estimate the disparity. Disparity discontinuities are introduced due to the sparse nature of stereo reconstruction, where surface fitting is performed at prominent facial points. We present our database of 99 sub- jects at different ranges where reconstruction and recogni- tion results are presented.

关键词： Passive Stereo System 3D Human Reconstruction Stereo pairs Recognition (Psychology) Cross correlation Face Face Acoustic equipment Reconstructive Surgical Procedures surface fitting acquisition system similar measure Reconstructions DISTANCE

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Rapid shallow coastal coral reef mapping using the teardrop system

Rapid shallow coastal coral reef mapping using the teardrop ...

引用

OCEANS 2012 MTS/IEEE Hampton Roads Conference: Harnessing the Power of the Ocean

作者： Corpuz, Francis James Naval Jr., Prospero Capili, Eusebio Jauod, Jaylord Judilla, Roel John Soriano, Maricor Vision and Image Processing Group National Institute of Physics University of the Philippines Diliman Quezon City Philippines Computer Vision and Machine Intelligence Group Department of Computer Science University of the Philippines Diliman Quezon City Philippines Mapua Robotics Center Institutional Laboratory Mgmt Office Mapua Institute of Technology Intramuros Manila Philippines

ISBN: (纸本)9781467308298

We present a rapid shallow coastal reef mapping system using a previously developed inexpensive diver less video capture system coupled with a fast-image mosaicking technique, using an affordable GPS logging device. The system replaces the traditional manta tow system of assessing and monitoring large areas of coastal coral reefs and at the same time provides historical visual record for future references. The system utilizes Teardrop, a hollow, teardrop-shaped that houses a commercial underwater point-and-shoot camera. The camera is set to video mode and captures video of the reef while the Teardrop is being towed by a wooden fishing boat. The resulting video is parsed into frames and mosaicked by using fast image labeling. The approximate location of the mosaicked images is recorded by using an inexpensive GPS logger. The coordinates are embedded on the mosaicked images and overlaid on mapping software such as Google Earth for visual record and spatial information integration. The same points are used to compute for the total distance covered by the capturing process. The whole process from coral reef video capture to mosaicking the images and finally embedding the mosaics in mapping software can be done in as short as 1 day, providing coastal managers and local government units with a tool to rapidly visualize and monitor shallow coral reefs. © 2012 IEEE.

关键词： Mapping

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Human action concentric video retrieval system using features weight updating method as relevance feedback

Human action concentric video retrieval system using feature...

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IEEE International Conference on Control System, Computing and Engineering (ICCSCE)

作者： Munaf Rashid S. A. R. Abu-Bakar Musa Mokji Aliyu Abdu Micro Electronics and Computer Engineering Department Computer Vision Videos and image processing Laboratory (CVVIP) Universiti Teknologi Malaysia Johor Bahru Malaysia

Retrieving videos based on its contents is becoming an increasingly popular area of research, because of enormous growth in the availability of multimedia information on public databases like Google and YouTube. Usually videos contain large variety of data but majority of online videos contain human as a subject of interest. In this paper, a human action based video retrieval system is presented which can be used to retrieve videos based on the contents of the query. The proposed system can search videos containing particular action on large databases efficiently. Furthermore, it is also shown that by using features weight updating approach as a Relevance feedback (RF), it is possible to involve user concepts interactively so that complex human action queries can be searched quickly to achieve useful results. Three popular Human action datasets namely Weizmann, KTH and UCF (sports) have been utilized in order to validate the performance of the proposed system. Experimental results and simulations show the efficacy of the proposed system. Even with number of visual challenges proposed approach will manage to get better accuracy as compare to other existing methods.

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2D PCA-based shape prior for level sets segmentation framework of the vertebral body

2D PCA-based shape prior for level sets segmentation framewo...

引用

Cairo International Biomedical Engineering Conference, CIBEC

作者： Ahmed Shalaby Melih Aslan Hossam Abdelmunim Aly A. Farag Computer Vision and Image Processing Laboratory University of Louisville KY USA Computer & Systems Engineering Department Ain Shams University Cairo Egypt

In this paper, a novel statistical shape modeling method is developed for the vertebral body (VB) segmentation framework. Two-dimensional principle component analysis (2D-PCA) technique is exploited to extract the shape prior. The obtained shape prior is then embedded into the image domain to develop a new shape-based segmentation approach. Our framework consists of four main steps: i) shape model construction using 2D-PCA, ii) Detection of the VB region using the Matched filter, iii) Initial segmentation using the graph cuts which integrates the intensity and spatial interaction models, and iv) Registration of the shape prior and initially segmented region to obtain the final segmentation. The proposed method is validated on a Phantom as well as clinical CT images with various Gaussian noise levels. The experimental results show that the noise immunity and the segmentation accuracy of 2D-PCA based approach are much higher than conventional PCA approach.

关键词： Shape image segmentation Training Principal component analysis Accuracy Computed tomography Vectors

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Produce recognition system using data mining algorithm

Produce recognition system using data mining algorithm

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IEEE International Conference on Control System, Computing and Engineering (ICCSCE)

作者： J. K. Chaw M. M. Mokji Computer Vision Video and Image Processing (CvviP) Laboratory Department of Microelectronic and Computer Engineering Faculty of Electrical Engineering Universiti Teknologi Malaysia Malaysia

Produce recognition system is a system that can categorize types of vegetables and fruits based on features extracted from the images. However, there are numerous features that can be extracted from fruits and vegetables such as colour, texture and shape. As a result, it is effort consuming to identify suitable features ad hoc. Thus, data mining is required to discover the most discriminative features for recognition. This paper aims to extend the usage of data mining algorithm to image domain. Data mining algorithm is preferred to other feature selection algorithms because it discovers nuggets of knowledge that can be understood by human whereas classic feature selection techniques provide outputs that can only be managed by learning algorithms.

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Varying pose face recognition using combination of discrete cosine & wavelet transforms

Varying pose face recognition using combination of discrete ...

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International Conference on Intelligent and Advanced Systems, ICIAS

作者： Seyed Omid Shahdi S. A. R. Abu-Bakar Computer Vision Video and Image Processing (CvviP) Research Laboratory Faculty of Electrical Engineering Universiti Teknologi Malaysia Skudai Johor Malaysia

Requirement for a person to face a camera for face identification process may no longer be necessary if the face recognition system is robust against variation of facial pose. In this paper, we proposed a face recognition method which remains reliable even in very large head pose variations. In this method, feature from local regions of face are extracted after employing both discrete cosine transform and discrete wavelet transform. Learning strategy is then applied to infer the relationship between face in a given pose and its frontal view. Results we obtained are very promising considering that our proposed method solely relies on a single gallery image. We also demonstrated the high performance of our method in a condition whereby the face images are of low-resolution quality.

关键词： Face Face recognition Vectors Discrete cosine transforms Discrete wavelet transforms Feature extraction Databases

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What Can an image of a Smooth Lambertian Surface Tell About Camera Nonlinearity?

What Can an Image of a Smooth Lambertian Surface Tell About ...

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Canadian Conference on computer and Robot vision, CRV

作者： Moumen T. El-Melegy Aly A. Farag Electrical Engineering Department Assiut University Asyut Egypt Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA

This paper investigates the use of a single image of a smooth Lambertian surface to calibrate and remove some image nonlinearities due to the imaging device. To the best of our knowledge, this has not been addressed before in the literature. We show that this is possible, both theoretically and practically, taking advantage of some local shading measures that vary nonlinearly as a function of luminance and geometric nonlinearities (e.g., gamma correction and lens distortion). This can work as a basis for developing a simple method to estimate these nonlinearities from a single image. Several experiments are reported to validate the proposed method.

关键词： Cameras Distortion measurement Lenses Calibration Shape Lighting Surface treatment

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DIRECT METHOD FOR SHAPE RECOVERY FROM POLARIZATION AND SHADING

DIRECT METHOD FOR SHAPE RECOVERY FROM POLARIZATION AND SHADI...

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IEEE International Conference on image processing

作者： Ali H. Mahmoud Moumen T. El-Melegy Aly A. Farag Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA Electrical Engineering Department Assiut University Assiut Egypt

Polarization imaging can give information about surface shape, and roughness. Polarization has been used for shape recovery, but with convex/concave reconstruction ambiguity. In this paper, we present a direct method to shape recovery using both polarization and shading that resolves this ambiguity, without the need for nonlinear optimization routines. Several experiments on synthetic and real datasets are reported to evaluate the proposed method. The method consistently outperforms some well-known methods based on polarization information alone.

关键词： Shape Surface reconstruction Azimuth image reconstruction Surface treatment Cameras

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