TY - CONF
T1 - Security evaluation for communication-friendly encryption of multimedia
T2 - Image Processing, 2004. ICIP '04. 2004 International Conference on
Y1 - 2004
A1 - Mao,Yinian
A1 - M. Wu
KW - access
KW - approximation
KW - atomic
KW - attacks;
KW - bitrate
KW - coding;
KW - communication-friendly
KW - communication;
KW - control;
KW - cryptography;
KW - data
KW - encryption
KW - encryption;
KW - generic
KW - joint
KW - method;
KW - metrics;
KW - multimedia
KW - multimedia-specific
KW - overhead;
KW - primitives;
KW - processing/cryptographic
KW - Security
KW - security;
KW - signal
KW - system;
KW - Telecommunication
KW - video
AB - 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.
JA - Image Processing, 2004. ICIP '04. 2004 International Conference on
VL - 1
M3 - 10.1109/ICIP.2004.1418818
ER -
TY - CONF
T1 - 3D face reconstruction from video using a generic model
T2 - Multimedia and Expo, 2002. ICME '02. Proceedings. 2002 IEEE International Conference on
Y1 - 2002
A1 - Chowdhury, A.R.
A1 - Chellapa, Rama
A1 - Krishnamurthy, S.
A1 - Vo, T.
KW - 3D
KW - algorithm;
KW - algorithms;
KW - analysis;
KW - Carlo
KW - chain
KW - Computer
KW - Face
KW - from
KW - function;
KW - generic
KW - human
KW - image
KW - Markov
KW - MCMC
KW - methods;
KW - model;
KW - Monte
KW - MOTION
KW - optimisation;
KW - OPTIMIZATION
KW - processes;
KW - processing;
KW - recognition;
KW - reconstruction
KW - reconstruction;
KW - sampling;
KW - sequence;
KW - sequences;
KW - SfM
KW - signal
KW - structure
KW - surveillance;
KW - video
KW - vision;
AB - 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.
JA - Multimedia and Expo, 2002. ICME '02. Proceedings. 2002 IEEE International Conference on
VL - 1
M3 - 10.1109/ICME.2002.1035815
ER -
TY - JOUR
T1 - A generic approach to simultaneous tracking and verification in video
JF - Image Processing, IEEE Transactions on
Y1 - 2002
A1 - Li,Baoxin
A1 - Chellapa, Rama
KW - approach;
KW - Carlo
KW - configuration;
KW - correspondence
KW - data;
KW - density
KW - density;
KW - estimated
KW - estimation;
KW - evaluation;
KW - extraction;
KW - Face
KW - facial
KW - feature
KW - generic
KW - human
KW - hypothesis
KW - image
KW - measurement
KW - methods;
KW - Monte
KW - object
KW - performance
KW - posterior
KW - probability
KW - probability;
KW - problem;
KW - processing;
KW - propagation;
KW - recognition;
KW - road
KW - sequence
KW - sequences;
KW - sequential
KW - signal
KW - space;
KW - stabilization;
KW - state
KW - synthetic
KW - temporal
KW - testing;
KW - tracking;
KW - vector;
KW - vehicle
KW - vehicles;
KW - verification;
KW - video
KW - visual
AB - 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.
VL - 11
SN - 1057-7149
CP - 5
M3 - 10.1109/TIP.2002.1006400
ER -
TY - CONF
T1 - The processing of form documents
T2 - Document Analysis and Recognition, 1993., Proceedings of the Second International Conference on
Y1 - 1993
A1 - David Doermann
A1 - Rosenfeld, A.
KW - AUTOMATIC
KW - business
KW - detectors;
KW - document
KW - documents;
KW - extraction;
KW - feature
KW - form
KW - forms;
KW - generation;
KW - generic
KW - handling;
KW - known
KW - markings;
KW - model
KW - modeling;
KW - non-form
KW - optimal
KW - properties;
KW - reconstruction;
KW - set;
KW - specialized
KW - stroke
KW - width
AB - 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
JA - Document Analysis and Recognition, 1993., Proceedings of the Second International Conference on
M3 - 10.1109/ICDAR.1993.395687
ER -