View subspaces for indexing and retrieval of 3D models

View-based indexing schemes for 3D object retrieval are gaining popularity since they provide good retrieval results. These schemes are coherent with the theory that humans recognize objects based on their 2D appearances. The viewbased techniques also allow users to search with various queries such as binary images, range images and even 2D sketches. The previous view-based techniques use classical 2D shape descriptors such as Fourier invariants, Zernike moments, Scale Invariant Feature Transform-based local features and 2D Digital Fourier Transform coefficients. These methods describe each object independent of others. In this work, we explore data driven subspace models, such as Principal Component Analysis, Independent Component Analysis and Nonnegative Matrix Factorization to describe the shape information of the views. We treat the depth images obtained from various points of the view sphere as 2D intensity images and train a subspace to extract the inherent structure of the views within a database. We also show the benefit of categorizing shapes according to their eigenvalue spread. Both the shape categorization and data-driven feature set conjectures are tested on the PSB database and compared with the competitor view-based 3D shape retrieval algorithmsComment: Three-Dimensional Image Processing (3DIP) and Applications (Proceedings Volume) Proceedings of SPIE Volume: 7526 Editor(s): Atilla M. Baskurt ISBN: 9780819479198 Date: 2 February 201

Compressively Sensed Image Recognition

Compressive Sensing (CS) theory asserts that sparse signal reconstruction is possible from a small number of linear measurements. Although CS enables low-cost linear sampling, it requires non-linear and costly reconstruction. Recent literature works show that compressive image classification is possible in CS domain without reconstruction of the signal. In this work, we introduce a DCT base method that extracts binary discriminative features directly from CS measurements. These CS measurements can be obtained by using (i) a random or a pseudo-random measurement matrix, or (ii) a measurement matrix whose elements are learned from the training data to optimize the given classification task. We further introduce feature fusion by concatenating Bag of Words (BoW) representation of our binary features with one of the two state-of-the-art CNN-based feature vectors. We show that our fused feature outperforms the state-of-the-art in both cases.Comment: 6 pages, submitted/accepted, EUVIP 201

Multi-Level Reversible Data Anonymization via Compressive Sensing and Data Hiding

Recent advances in intelligent surveillance systems have enabled a new era of smart monitoring in a wide range of applications from health monitoring to homeland security. However, this boom in data gathering, analyzing and sharing brings in also significant privacy concerns. We propose a Compressive Sensing (CS) based data encryption that is capable of both obfuscating selected sensitive parts of documents and compressively sampling, hence encrypting both sensitive and non-sensitive parts of the document. The scheme uses a data hiding technique on CS-encrypted signal to preserve the one-time use obfuscation matrix. The proposed privacy-preserving approach offers a low-cost multi-tier encryption system that provides different levels of reconstruction quality for different classes of users, e.g., semi-authorized, full-authorized. As a case study, we develop a secure video surveillance system and analyze its performance.publishedVersionPeer reviewe

Reproducible Research in Signal Processing

Reproducible research results become more and more an important issue as systems under investigation are growing permanently in complexity, and it becomes thus almost impossible to judge the accuracy of research results merely on the bare paper presentation.Peer ReviewedPreprin

Sign Language Tutoring Tool

In this project, we have developed a sign language tutor that lets users learn isolated signs by watching recorded videos and by trying the same signs. The system records the user's video and analyses it. If the sign is recognized, both verbal and animated feedback is given to the user. The system is able to recognize complex signs that involve both hand gestures and head movements and expressions. Our performance tests yield a 99% recognition rate on signs involving only manual gestures and 85% recognition rate on signs that involve both manual and non manual components, such as head movement and facial expressions.Comment: eNTERFACE'06. Summer Workshop. on Multimodal Interfaces, Dubrovnik : Croatie (2007

Digital multifrequency receivers using nonlinear spectral estimation

Le récepteur à multiples fréquences est une composante importante pour l'interface entre des réseaux analogues et numériques. De nouvelles solutions au problème du récepteur à multiples fréquences ont été étudiées. Les nouvelles solutions sont basées sur l'estimation paramétrique d'un spectre autoregressive. Les spectres sont estimés à partir d'échantillons de longueurs finies. Les diverses fréquences sont obtenues en détectant la position des maximums et le contenu énergétique des valeurs pointes. Cette étude est basée sur les résultats de simulations pour diverses combinaisons de fréquences et de bruit. Les performances des algorithmes d'estimation des spectres ont été classées en fonction de leurs probabilités d'erreurs et de leurs efficacités en fonction de la taille de l'échantillonnage. L'estimation de spectres autorégressifs par la methode d'auto correlation s'avère être une alternative intéressante au problème de la détection de fréquence par rapport aux solutions existantes. De nouveaux développements dans l'application de cette technique sont à suivre

Data compression of speech signals by variable rate sampling

Dans ce travail, les quantificateurs séquentiels avec taux d'échantillonage dépendent du signal d'entrée ont été étudiés. Les propriétés d'un modulateur à delta asynchrone pour le codage efficace de la parole ont été analysées en particulier. Le signal d'entrée est échantilloné à taux non-uniforme et dans une manière adaptative. En conséquence ce signal est converti dans un processus d'intervalles interbit, lequel est comprimé, mis dans un mémoire tampon et transmis par multiplexage avec la séquence des polarités. Nous avons aussi étudié differentes stratégies d'adaptation. La performance de ce scheme est characterisée par le rapport signal-bruit et par un facteur de sur-échantillonage. Cette étude est basé surtout sur des travaux de simulation extensives en utilisant des processus aléatoires dont la form d'onde ressemble à celle de la parole naturelle

Strict integrity control of biomedical images

International audienceThe control of the integrity and authentication of medical images is becoming ever more important within the Medical Information Systems (MIS). The intra- and interhospital exchange of images, such as in the PACS (Picture Archiving and Communication Systems), and the ease of copying, manipulation and distribution of images have brought forth the security aspects. In this paper we focus on the role of watermarking for MIS security and address the problem of integrity control of medical images. We discuss alternative schemes to extract verification signatures and compare their tamper detection performance