Robust Face Recognition from Multi-View Videos

Abstract

Multiview face recognition has become an active research area in the last few years. In this paper, we present an approach for video-based face recognition in camera networks. Our goal is to handle pose variations by exploiting the redundancy in the multiview video data. However, unlike traditional approaches that explicitly estimate the pose of the face, we propose a novel feature for robust face recognition in the presence of diffuse lighting and pose variations. The proposed feature is developed using the spherical harmonic representation of the face texture-mapped onto a sphere; the texture map itself is generated by back-projecting the multiview video data. Video plays an important role in this scenario. First, it provides an automatic and efficient way for feature extraction. Second, the data redundancy renders the recognition algorithm more robust. We measure the similarity between feature sets from different videos using the reproducing kernel Hilbert space. We demonstrate that the proposed approach outperforms traditional algorithms on a multiview video database.

Domain : Image Processing

Contact Detail

Ph.no : 7200555526

e-mail id : info.nanosoftwares@gmail.com

Discrete Anamorphic Transform for Image Compression

Abstract

To deal with the exponential increase of digital data, new compression technologies are needed for more efficient representation of information. We introduce a physics-based transform that enables image compression by increasing the spatial coherency. We also present the Stretched Modulation Distribution, a new density function that provides the recipe for the proposed image compression. Experimental results show pre-compression using our method can improve the performance of JPEG 2000 format.

Segmentation-Driven Image Registration- Application to 4D DCE-MRI Recordings of the Moving Kidneys

Abstract

Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) of the kidneys requires proper motion correction and segmentation to enable an estimation of glomerular filtration rate through pharmacokinetic modeling. Traditionally, co-registration, segmentation, and pharmacokinetic modeling have been applied sequentially as separate processing steps. In this paper, a combined 4D model for simultaneous registration and segmentation of the whole kidney is presented. To demonstrate the model in numerical experiments, we used normalized gradients as data term in the registration and a Mahalanobis distance from the time courses of the segmented regions to a training set for supervised segmentation. By applying this framework to an input consisting of 4D image time series, we conduct simultaneous motion correction and two-region segmentation into kidney and background. The potential of the new approach is demonstrated on real DCE-MRI data from ten healthy volunteers.

Domain : Image Processing

Contact Detail 

Ph.no : 7200555526

e-mail id : info.nanosoftwares@gmail.com

P-FAD: Real-Time Face Detection Scheme on Embedded Smart Camera

Abstract

            Face detection on general embedded devices is fundamentally different from the conventional approach on personal computer or consumer digital camera due to the limited computation and power capacity. The resource-limited characteristic gives rise to new challenges for implementing a real-time video surveillance system with smart cameras. In this work, we present the design and implementation of Pyramid-like FAce Detection (P-FAD), a real-time face detection system constructed on general embedded devices. Motivated by the observation that the computation overhead increases proportionally to its pixel manipulation, P-FAD proposes a hierarchical approach to shift the complex computation to the promising regions. More specifically, P-FAD present a three-stage coarse, shift, and refine procedure, to construct a pyramid-like detection framework for reducing the computation overhead significantly. This framework also strikes a balance between the detection speed and accuracy. We have implemented P-FAD on notebook, Android phone and our embedded smart camera platform. An extensive system evaluation in terms of detailed experimental and simulation results is provided. Our empirical evaluation shows that P-FAD outperforms V-J detector calibrated color detector (VJ-CD) and color detector followed by a V-J detector (CD-VJ), the state of the art real-time face detection techniques by 4.7 –8.6 on notebook and by up to 8.2 on smart phone in terms of the detection speed.

Domain : Image Processing

Contact Details

Ph.no : 7200555526

e-mail id : info.nanosoftwares@gmail.com

An Unbiased Risk Estimator for Image Denoising in the Presence of Mixed Poisson–Gaussian Noise

Abstract

            The behavior and performance of denoising algorithms are governed by one or several parameters, whose optimal settings depend on the content of the processed image and the characteristics of the noise, and are generally designed to minimize the mean squared error (MSE) between the denoised image returned by the algorithm and a virtual ground truth. In this paper, we introduce a new Poisson-Gaussian unblased risk estimator (PG-URE) of the MSE applicable to a mixed Poisson-Gaussian noise model that unifies the widely used Gaussian and Poisson noise model in fluorescence bioimaging applications. We propose a stochastic methodology to evaluate this estimator in the case when little is known about the internal machinery of the considered denoising algorithm, and we analyze both theoretically and empirically the characteristics of the PG-URE estimator. Finally, we evaluate the PG-URE-driven parametrization for three standard denoising algorithms, with and without variance stabilizing tranforms, and different characteristics of the Poisson-Gaussian noise mixture.

Domain : Image Processing

Contact Details

Ph.no : 7200555526

e-mail id : info.nanosoftwares@gmail.com

Decentralized Computation Offloading Game For Mobile Cloud Computing

Abstract

Mobile cloud computing is envisioned as a promising approach to augment computation capabilities of mobile devices for emerging resource-hungry mobile applications. In this paper, we propose a game theoretic approach for achieving efficient computation offloading for mobile cloud computing. We formulate the decentralized computation offloading decision making problem among mobile device users as a decentralized computation offloading game. We analyze the structural property of the game and show that the game always admits a Nash equilibrium. We then design a decentralized computation offloading mechanism that can achieve a Nash equilibrium of the game and quantify its efficiency ratio over the centralized optimal solution. Numerical results demonstrate that the proposed mechanism can achieve efficient computation offloading performance and scale well as the system size increases.

Domain : Mobile Computing

Contact Detail

Ph.no : 7200555526

e-mail id : info.nanosoftwares@gmail,com

Captcha as Graphical Passwords—A New Security Primitive Based on Hard AI Problems

Abstract

Many security primitives are based on hard mathematical problems. Using hard AI problems for security is emerging as an exciting new paradigm, but has been underexplored. In this paper, we present a new security primitive based on hard AI problems, namely, a novel family of graphical password systems built on top of Captcha technology, which we call Captcha as graphical passwords (CaRP). CaRP is both a Captcha and a graphical password scheme. CaRP addresses a number of security problems altogether, such as online guessing attacks, relay attacks, and, if combined with dual-view technologies, shoulder-surfing attacks. Notably, a CaRP password can be found only probabilistically by automatic online guessing attacks even if the password is in the search set. CaRP also offers a novel approach to address the well-known image hotspot problem in popular graphical password systems, such as PassPoints, that often leads to weak password choices. CaRP is not a panacea, but it offers reasonable security and usability and appears to fit well with some practical applications for improving online security.

Domain : Network Security

Contact Details 

Ph.no : 7200555526

e-mail : info.nanosoftwares@gmail.com

Secure Data Retrieval for Decentralized Disruption-Tolerant Military Networks

Abstract

      Mobile nodes in military environments such as a battlefield or a hostile region are likely to suffer from intermittent network connectivity and frequent partitions. Disruption-tolerant network (DTN) technologies are becoming successful solutions that allow wireless devices carried by soldiers to communicate with each other and access the confidential information or command reliably by exploiting external storage nodes. Some of the most challenging issues in this scenario are the enforcement of authorization policies and the policies update for secure data retrieval. Ciphertext-policy attribute-based encryption (CP-ABE) is a promising cryptographic solution to the access control issues. However, the problem of applying CP-ABE in decentralized DTNs introduces several security and privacy challenges with regard to the attribute revocation, key escrow, and coordination of attributes issued from different authorities. In this paper, we propose a secure data retrieval scheme using CP-ABE for decentralized DTNs where multiple key authorities manage their attributes independently. We demonstrate how to apply the proposed mechanism to securely and efficiently manage the confidential data distributed in the disruption-tolerant military network.

Domain : Networking

Contact Details

Ph. no : 7200555526

e-mail : info.nanosoftwares@gmail.com

NCCloud: A Network-Coding-Based Storage System in a Cloud-of-Clouds

Abstract

To provide fault tolerance for cloud storage, recent studies propose to stripe data across multiple cloud vendors. However, if a cloud suffers from a permanent failure and loses all its data, we need to repair the lost data with the help of the other surviving clouds to preserve data redundancy. We present a proxy-based storage system for fault-tolerant multiple-cloud storage called NCCloud, which achieves cost-effective repair for a permanent single-cloud failure. NCCloud is built on top of a network-coding-based storage scheme called the functional minimum-storage regenerating (FMSR) codes, which maintain the same fault tolerance and data redundancy as in traditional erasure codes (e.g., RAID-6), but use less repair traffic and, hence, incur less monetary cost due to data transfer. One key design feature of our FMSR codes is that we relax the encoding requirement of storage nodes during repair, while preserving the benefits of network coding in repair. We implement a proof-of-concept prototype of NCCloud and deploy it atop both local and commercial clouds. We validate that FMSR codes provide significant monetary cost savings in repair over RAID-6 codes, while having comparable response time performance in normal cloud storage operations such as upload/download.

Domain : Cloud Computing

Contact Details 

Ph. no : 7200555526

e-mail : info.nanosoftwares@gmail.com