The Multiscenario Multienvironment BioSecure Multimodal Database (BMDB)

Autor: Lale Akarun, Bernadette Dorizzi, Javier Ortega-Garcia, Joaquin Gonzalez-Rodriguez, Bao Ly-Van, Sonia Garcia-Salicetti, Arman Savran, Harald Ganster, M.R. Freire, Jonas Richiardi, Josef Kittler, Andrezj Drygajlo, Javier Galbally, Massimo Tistarelli, Sri-Kaushik Pavani, Jean Hennebert, J.L. Alba-Castro, Fernando Alonso-Fernandez, Linda Brodo, Thirimachos Bourlai, Lorene Allano, Enrique Otero-Muras, Elisardo González-Agulla, Michael Fairhurst, Alejandro F. Frangi, Ming Ng, Julian Fierrez, Norman Poh, Farzin Deravi, Carmen García-Mateo, Federico M. Sukno, Andreas Humm

Publikováno v: IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence, Institute of Electrical and Electronics Engineers, 2010, 32 (6), pp.1097-1111. ⟨10.1109/TPAMI.2009.76⟩
Recercat. Dipósit de la Recerca de Catalunya
instname

A new multimodal biometric database designed and acquired within the framework of the European BioSecure Network of Excellence is presented. It is comprised of more than 600 individuals acquired simultaneously in three scenarios: 1) over the Internet

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cf3b6ee34eb42451404569cd34761df6
http://arxiv.org/abs/2111.08702

Gaussian weak classifiers based on co-occurring Haar-like features for face detection

Autor: David Delgado-Gómez, Sri-Kaushik Pavani, Alejandro F. Frangi

Publikováno v: Pattern Analysis and Applications. 17:431-439

Recently, in the context of appearance-based face detection, it has been shown by Mita et al. that weak classifiers based on co-occurring, or multiple, Haar-like features provide better speed-accuracy trade-off than the widely used Viola and Jones's

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::447ad34ff8d2b2e6f1bb737b6ea3d1e3
https://doi.org/10.1007/s10044-012-0295-5

Quality metric for Parasternal Long AXis B-mode echocardiograms

Autor: Sri-Kaushik, Pavani, Navneeth, Subramanian, Mithun, Das Gupta, Pavan, Annangi, Satish C, Govind, Brian, Young

Publikováno v: Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. 15(Pt 2)

This paper presents a method for automatically estimating the quality of Parasternal Long AXis (PLAX) B-mode echocardiograms. The purpose of the algorithm is to provide live feedback to the user on the quality of the acquired image. The proposed appr

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid________::521d831aefeb3069c27dcfc55498dd26
https://pubmed.ncbi.nlm.nih.gov/23286083

A Confidence-Based Update Rule for Self-updating Human Face Recognition Systems

Autor: Alejandro F. Frangi, Sri-Kaushik Pavani, Federico M. Sukno, Constantine Butakoff, Xavier Planes

Publikováno v: Advances in Biometrics ISBN: 9783642017926
ICB

The aim of this paper is to present an automatic update rule to make a face recognition system adapt itself to the continuously changing appearance of users. The main idea is that every time the system interacts with a user, it adapts itself to inclu

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::ceab1748a339a2a5281f03f650f89d00
https://doi.org/10.1007/978-3-642-01793-3_16

Gaussian Weak Classifiers Based on Haar-Like Features with Four Rectangles for Real-time Face Detection

Autor: David Delgado Gomez, Alejandro F. Frangi, Sri-Kaushik Pavani

Publikováno v: Computer Analysis of Images and Patterns ISBN: 9783642037665
CAIP

This paper proposes Gaussian weak classifiers (GWCs) for use in real-time face detection systems. GWCs are based on Haar-like features (HFs) with four rectangles (HF4s), which constitute the majority of the HFs used to train a face detector. To label

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::b4083030296a522ba66f18cd68386a10
https://doi.org/10.1007/978-3-642-03767-2_11