%0 Conference Paper
%B Image Processing, 2004. ICIP '04. 2004 International Conference on
%D 2004
%T Security evaluation for communication-friendly encryption of multimedia
%A Mao,Yinian
%A M. Wu
%K access
%K approximation
%K atomic
%K attacks;
%K bitrate
%K coding;
%K communication-friendly
%K communication;
%K control;
%K cryptography;
%K data
%K encryption
%K encryption;
%K generic
%K joint
%K method;
%K metrics;
%K multimedia
%K multimedia-specific
%K overhead;
%K primitives;
%K processing/cryptographic
%K Security
%K security;
%K signal
%K system;
%K Telecommunication
%K video
%X This paper addresses the access control issues unique to multimedia, by using a joint signal processing and cryptographic approach to multimedia encryption. Based on three atomic encryption primitives, we present a systematic study on how to strategically integrate different atomic operations to build a video encryption system. We also propose a set of multimedia-specific security metrics to quantify the security against approximation attacks and to complement the existing notion of generic data security. The resulting system can provide superior performance to both generic encryption and its simple adaptation to video in terms of a joint consideration of security, bitrate overhead, and communication friendliness.
%B Image Processing, 2004. ICIP '04. 2004 International Conference on
%V 1
%P 569 - 572 Vol. 1 - 569 - 572 Vol. 1
%8 2004/10//
%G eng
%R 10.1109/ICIP.2004.1418818
%0 Conference Paper
%B Multimedia and Expo, 2002. ICME '02. Proceedings. 2002 IEEE International Conference on
%D 2002
%T 3D face reconstruction from video using a generic model
%A Chowdhury, A.R.
%A Chellapa, Rama
%A Krishnamurthy, S.
%A Vo, T.
%K 3D
%K algorithm;
%K algorithms;
%K analysis;
%K Carlo
%K chain
%K Computer
%K Face
%K from
%K function;
%K generic
%K human
%K image
%K Markov
%K MCMC
%K methods;
%K model;
%K Monte
%K MOTION
%K optimisation;
%K OPTIMIZATION
%K processes;
%K processing;
%K recognition;
%K reconstruction
%K reconstruction;
%K sampling;
%K sequence;
%K sequences;
%K SfM
%K signal
%K structure
%K surveillance;
%K video
%K vision;
%X Reconstructing a 3D model of a human face from a video sequence is an important problem in computer vision, with applications to recognition, surveillance, multimedia etc. However, the quality of 3D reconstructions using structure from motion (SfM) algorithms is often not satisfactory. One common method of overcoming this problem is to use a generic model of a face. Existing work using this approach initializes the reconstruction algorithm with this generic model. The problem with this approach is that the algorithm can converge to a solution very close to this initial value, resulting in a reconstruction which resembles the generic model rather than the particular face in the video which needs to be modeled. We propose a method of 3D reconstruction of a human face from video in which the 3D reconstruction algorithm and the generic model are handled separately. A 3D estimate is obtained purely from the video sequence using SfM algorithms without use of the generic model. The final 3D model is obtained after combining the SfM estimate and the generic model using an energy function that corrects for the errors in the estimate by comparing local regions in the two models. The optimization is done using a Markov chain Monte Carlo (MCMC) sampling strategy. The main advantage of our algorithm over others is that it is able to retain the specific features of the face in the video sequence even when these features are different from those of the generic model. The evolution of the 3D model through the various stages of the algorithm is presented.
%B Multimedia and Expo, 2002. ICME '02. Proceedings. 2002 IEEE International Conference on
%V 1
%P 449 - 452 vol.1 - 449 - 452 vol.1
%8 2002///
%G eng
%R 10.1109/ICME.2002.1035815
%0 Journal Article
%J Image Processing, IEEE Transactions on
%D 2002
%T A generic approach to simultaneous tracking and verification in video
%A Li,Baoxin
%A Chellapa, Rama
%K approach;
%K Carlo
%K configuration;
%K correspondence
%K data;
%K density
%K density;
%K estimated
%K estimation;
%K evaluation;
%K extraction;
%K Face
%K facial
%K feature
%K generic
%K human
%K hypothesis
%K image
%K measurement
%K methods;
%K Monte
%K object
%K performance
%K posterior
%K probability
%K probability;
%K problem;
%K processing;
%K propagation;
%K recognition;
%K road
%K sequence
%K sequences;
%K sequential
%K signal
%K space;
%K stabilization;
%K state
%K synthetic
%K temporal
%K testing;
%K tracking;
%K vector;
%K vehicle
%K vehicles;
%K verification;
%K video
%K visual
%X A generic approach to simultaneous tracking and verification in video data is presented. The approach is based on posterior density estimation using sequential Monte Carlo methods. Visual tracking, which is in essence a temporal correspondence problem, is solved through probability density propagation, with the density being defined over a proper state space characterizing the object configuration. Verification is realized through hypothesis testing using the estimated posterior density. In its most basic form, verification can be performed as follows. Given a measurement vector Z and two hypotheses H_{1} and H0, we first estimate posterior probabilities P(H_{0}|Z) and P(H_{1}|Z), and then choose the one with the larger posterior probability as the true hypothesis. Several applications of the approach are illustrated by experiments devised to evaluate its performance. The idea is first tested on synthetic data, and then experiments with real video sequences are presented, illustrating vehicle tracking and verification, human (face) tracking and verification, facial feature tracking, and image sequence stabilization.
%B Image Processing, IEEE Transactions on
%V 11
%P 530 - 544
%8 2002/05//
%@ 1057-7149
%G eng
%N 5
%R 10.1109/TIP.2002.1006400
%0 Conference Paper
%B Document Analysis and Recognition, 1993., Proceedings of the Second International Conference on
%D 1993
%T The processing of form documents
%A David Doermann
%A Rosenfeld, A.
%K AUTOMATIC
%K business
%K detectors;
%K document
%K documents;
%K extraction;
%K feature
%K form
%K forms;
%K generation;
%K generic
%K handling;
%K known
%K markings;
%K model
%K modeling;
%K non-form
%K optimal
%K properties;
%K reconstruction;
%K set;
%K specialized
%K stroke
%K width
%X An overview of an approach to the generic modeling and processing of known forms is presented. The system provides a methodology by which models are generated from regions in the document based on their usage. Automatic extraction of an optimal set of features to be used for registration is proposed, and it is shown how specialized detectors can be designed for each feature based on their position, orientation and width properties. Registration of the form with the model is accomplished using probing to establish correspondence. Form components which are corrupted by markings are detected and isolated, the intersections are interpreted and the properties of the non-form markings are used to reconstruct the strokes through the intersections. The feasibility of these ideas is demonstrated through an implementation of key components of the system
%B Document Analysis and Recognition, 1993., Proceedings of the Second International Conference on
%P 497 - 501
%8 1993/10//
%G eng
%R 10.1109/ICDAR.1993.395687