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Privacy & Security Issues Related to Match Scores

Privacy & Security Issues Related to Match Scores

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： P. Mohanty S. Sarkar R. Kasturi Computer Science and Engineering University of South Florida Tampa FL USA

Security and privacy issues remains a major hurdle in wide deployment of biometric based authentication system. For example, unauthorized access or regeneration of face templates has serious implications on the privacy of the concerned users. For robust and practical implementation of such system it is necessary to identify and explore the possible ways by which reconstruction of template is feasible. In this paper, we show that even match scores carries sufficient information for reconstruction of the original face templates. We propose a novel non-iterative scheme to reconstruct face templates from match scores. We use an affine transformation of the images to approximate the behavior of a given face recognition system using an independent set of face templates termed as "break-in" set. Selected templates from the break-in set are matched only once with the enrolled template of the target account and match scores are recorded. These scores are then embedded in the approximating affine space along with break-in set templates to compute the co-ordinates of the target template. The inverse transformation is used to reconstruct the original target template. We present the reconstruction of templates for a commercial off the shelf (COTS) face recognition system. The COTS system is set to operate at 1% False Acceptance Rate and 99% True Acceptance Rate with 100 enrollments. We observed that with proposed scheme, at most 450 attempts are required to achieve a 0.93 probability of break into the COTS face recognition system by choosing a random gallery target.

关键词： Privacy Biometrics Image reconstruction Authentication Robustness Face recognition computer science computer security Embedded computing Availability

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Robust Moving Object Detection at Distance in the Visible Spectrum and Beyond Using A Moving Camera

Robust Moving Object Detection at Distance in the Visible Sp...

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Yan Zhang S.J. Kiselewich W.A. Bauson R. Hammoud Delphi Electronics and Safety Kokomo IN USA

Automatic detection of moving objects at distance and in all weather conditions is a critical task in many visionbased safety applications such as video surveillance and vehicle forewarn collision warning. In such applications, prior knowledge about the object class (vehicle, pedestrian, tree, etc.) and imaging conditions (shadow, depth) is unavailable. What makes the task even more challenging is when the camera is non-stationary, e.g., mounted on a moving vehicle. The essential problem in this case lies in distinguishing between camera-induced motion and independent motion. This paper proposes a robust algorithm for automatic moving object detection at distance. The camera is mounted on a moving vehicle and operates in both day and night time. Through the utilization of the focus of expansion (FOE) and its associated residual map, the proposed method is able to detect and separate independently moving objects (IMOs) from the "moving" background caused by the camera motion. Experimentations on numerous realworld driving videos have shown the effectiveness of the proposed technique. Moving objects such as pedestrians and vehicles up to 40 meters away from the camera have been reliably detected at 10 frames per second on a 1.8GHz PC.

关键词： Robustness Object detection Cameras Vehicle safety Motion detection Motion estimation Vehicle detection Video surveillance pattern recognition Subtraction techniques

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Segmentation of Vessels Using Weighted Local Variances and an Active contour Model

Segmentation of Vessels Using Weighted Local Variances and a...

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： W.K. Law A.C.S. Chung Lo Kwee-Seong Medical Image Analysis Laboratory Department of Computer Science Hong Kong University of Science and Technology Hong Kong China

Performing segmentation of vasculature with blurry and low contrast boundaries in noisy images is a challenging problem. This paper presents a novel approach to segmenting blood vessels using weighted local variances and an active contour model. In this work, the vessel boundary orientation is estimated locally based on the orientation that minimizes the weighted local variance. Such estimation is less sensitive to noise compared with other common approaches. The edge clearness is measured by the ratio of weighted local variances obtained along different orientations. It is independent of the edge intensity contrast and capable of locating weak boundaries. Integrating the orientation and clearness of edges, an active contour model is employed to align contours that match the contour tangent direction and edge orientation. The proposed method is validated by two synthetic images and two real cases. It is experimentally shown that our method is suitable for dealing with noisy images which consist of structures having blurry and low contrast boundaries, such as blood vessels.

关键词： Active contours Image segmentation Biomedical imaging Image edge detection Blood vessels Angiography Laboratories computer science Active noise reduction Level set

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Protecting Face Biometric Data on Smartcard with Reed-Solomon Code

Protecting Face Biometric Data on Smartcard with Reed-Solomo...

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Yi Cheng Feng P.C. Yuen Department of Computer Science Hong Kong Baptist University Hong Kong China

This paper addresses the biometric security problem on smartcard and proposes a new method to protect face biometric data against attack. The proposed method is developed based on the Reed-Solomon codes, with two modifications. First, to handle the image variations problem, a bounded distance encoding algorithm is used to reduce the within-class distance. Second, since the dimension of the face feature vector is relatively large, we divide the feature vector into smaller segment. In this way, we found that it will not only affect the performance, but also the security of the encoding algorithm. A theoretical analysis is also given in this paper. Two most popular appearance-basedmethods, namely, Eigenface and Fisherface, are selected to construct the feature vector and ORL database is used for evaluation. In Eigenface system, the proposed algorithm offers a security level of 120 bits, with an acceptable error rate of around 3%. In Fisherface system, the proposed algorithm offers a security level of 62 bits, with equal error rate around 5%. The results are comparable with performance of Eigenface and Fisherface without protection.

关键词： Protection Bioinformatics Reed-Solomon codes Data security Error analysis Biometrics Image coding Image segmentation Encoding Spatial databases

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Peg-Free Hand Shape Verification Using High Order Zernike Moments

Peg-Free Hand Shape Verification Using High Order Zernike Mo...

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： G. Amayeh G. Bebis A. Erol M. Nicolescu Computer Vision Laboratory University of Nevada Reno NV USA

Hand-based verification is a key biometric technology with a wide range of potential applications both in industry and government. The focus of this work is on improving the efficiency, accuracy, and robustness of hand-based verification. In particular, we propose using high-order Zernike moments to represent hand geometry, avoiding the more difficult and prone to errors process of hand-landmark extraction (e.g., finding finger joints). The proposed system operates on 2D hand silhouette images acquired by placing the hand on a planar lighting table without any guidance pegs, increasing the ease of use compared to conventional systems. Zernike moments are powerful translation, rotation, and scale invariant shape descriptors. To deal with several practical issues related to the computation of highorder Zernike moments including computational cost and lack of accuracy due to numerical errors, we have employed an efficient algorithm that uses arbitrary precision arithmetic, a look-up table, and avoids recomputing the same terms multiple times [2]. The proposed hand-based authentication system has been tested on a database of 40 subjects illustrating promising results. Qualitative comparisons with state of the art systems illustrate comparable of better performance.

关键词： Shape Biometrics Government Focusing Robustness Geometry Fingers Computational efficiency Arithmetic Table lookup

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Transitivity-based Removal of Correspondence Outliers for Motion Analysis

Transitivity-based Removal of Correspondence Outliers for Mo...

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： A. Robles-Kelly Y. Moses NICTA Canberra ACT Australia School of Computer Science Interdisciplinary Center Herzliya Israel

In this paper we address the problem of removing correspondence outliers in a sequence of images. The input to the system is a set of putative matches which are based upon image-feature similarity. Classical methods for outlier removal, such as RANSAC-based approaches, assume consistency and rigidity in the scene motion between two or three frames in the sequence. Here we propose a novel method for removing correspondence outliers that does not depend on such assumptions. Our method is based on the observation that correspondence is an equivalence relation, and, hence, transitivity must hold between corresponding features in different frames. We impose consistency on the transitivity by representing the matching information as a weighted graph with positive and negative edge-weights. Consistency is then enforced by partitioning the nodes in the graph so as to remove edges corresponding to falsepositive correspondences. The clustering algorithm is of spectral nature and can handle graphs whose edge-weights are non-positive. Our method is a general one that can be used for purposes of outlier removal from correspondences between any entities whose putative matches imply equivalence relations. We illustrate the utility of the method for purposes of outlier removal on a real-world image sequence and compare our results with those yield using an alternative.

关键词： Motion analysis Australia Layout Image sequences Tracking Shape computer science Clustering algorithms Partitioning algorithms pattern matching

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vision-Based Projection-Handwriting Integration in Classroom

Vision-Based Projection-Handwriting Integration in Classroom

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Weihong Li Hao Tang Zhigang Zhu Graduate Center City University of New York New York NY USA City College City University of New York New York NY USA Graduate Center & City College City University of New York New York NY USA

A projector based presentation and a whiteboard handwriting capture system, when monitored by a camera, could provide a better means to present a lecture in a classroom and later to deliver more effective e-lectures for off-campus students. When the PowerPoint© (PPT) slides are projected on the whiteboard where the instructor annotates, modifies, or expands the PPT presentation, geometrically registering high-resolution images from the two sources yields high quality digital presentations. Since the two sources do not share the same materials, one with printing notes and the other with handwriting notes, a digital camera is used as a bridge to align the two sources, as well as to record the whole lecture. We present a hybrid registration approach to align the PPT and handwriting images and then propose a coarse-to-fine content matching method to register handwriting contents captured by the video camera and the whiteboard capture system. We also show an integrated user-customized presentation system to provide students better lecturing context. Experimental results are presented to validate our approach, and future research directions are also discussed.

关键词： Cameras Cities and towns Educational institutions computer vision Switches Video sharing Sensor systems Ink Timing HTML

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Fast Image Motion Computation on an Embedded computer

Fast Image Motion Computation on an Embedded Computer

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： X. Lu R. Manduchi University of California Santa Cruz USA

Wireless, battery-powered camera networks are becoming of interest for surveillance and monitoring applications. The computational power of these platforms is often limited in order to reduce energy consumption. Among the visual tasks that the onboard processor may be required to perform, motion analysis is one of the most basic and relevant. Knowledge of the direction of motion and velocity of a moving body may be used to take actions such as sending an alarm or triggering other camera nodes in the network. We present a fast algorithm for identifying moving areas in an image and computing the average velocity in such areas. The algorithm, which was implemented and tested on a Crossbow Stargate embedded platform, is comprised of three stages. First, local differential measurements are used to determine an initial labeling of image blocks. A total least squares approach is proposed, with fast implementation inspired by the work of Benedetti and Perona. Then, belief propagation is used to impose spatial coherence and resolve aperture effect inherent in textureless areas. Finally, the velocity of the resulting blobs is estimated via least squares regression. A detailed analysis of timing and power consumption characteristics of this algorithm is also presented.

关键词： Embedded computing Cameras Energy consumption Surveillance computerized monitoring Application software computer applications Motion analysis Testing Labeling

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Semantic Event Detection using Conditional Random Fields

Semantic Event Detection using Conditional Random Fields

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Tao Wang Jianguo Li Qian Diao Wei Hu Yimin Zhang C. Dulong Intel China Research Center Limited Beijing China Intel Corporation Santa Clara CA USA

Semantic event detection is an active research field of video mining in recent years. One of the challenging problems is how to effectively model temporal and multi-modality characteristics of video. In this paper, we employ Conditional Random Fields (CRFs) to fuse temporal multi-modality cues for event detection. CRFs are undirected probabilistic models designed for segmenting and labeling sequence data. Compared with traditional SVM and Hidden Markov Models (HMMs), CRFs based event detection offers several particular advantages including the abilities to relax strong independence assumptions in the state transition and avoid a fundamental limitation of directed graphical models. To detect event, we use a three-level framework based on multi-modality fusion and mid-level keywords. The first level extracts audiovisual features, the mid-level detects semantic keywords, and the high-level infers semantic events from multiple keyword sequences. The experimental results from soccer highlights detection demonstrate that CRFs achieves better performance particularly in slice level measure.

关键词： Event detection Hidden Markov models Labeling Support vector machines computer vision Support vector machine classification Bayesian methods Decoding Fuses Graphical models

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BICIR:Boundary-Constrained Inverse Consistent Image Registration Using WEB-Splines

BICIR:Boundary-Constrained Inverse Consistent Image Registra...

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IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： D. Kumar Xiujuan Geng E.A. Hoffman G.E. Christensen Department of Electrical and Computer Engineering University of Iowa Iowa IA USA Department of Radiology University of Iowa Iowa IA USA

We present a new registration method called boundaryconstrained inverse consistent image registration (BICIR). This method is novel because it performs boundary constrained intensity based image registration by combining surface- and intensity-based registration. The method registers a region of interest and ignores everything outside the region eliminating interference caused by surrounding regions. The boundaries of the two objects are first registered using the transitive inverse-consistent manifold registration (TICMR) described in [4]. This provides the boundary conditions, which are used to compute the displacement over the object using the Element Free Galerkin Method (EFGM). The EFGM solution is used as an initialization and is fine-tuned using the intensity information inside the object. The transformations are represented with shape specific basis functions that have local support. These basis functions are defined only over the region of interest and help improve the computational performance. The BICIR method was tested for a number of 2-dimensional test images. The method was validated using the similarity cost, relative overlap and inverse consistency error.

关键词： Image registration Registers Cities and towns Moment methods Shape Testing Radiology Interference constraints Interference elimination Boundary conditions

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