11 research outputs found
The AVA Multi-View Dataset for Gait Recognition
In this paper, we introduce a new multi-view dataset for
gait recognition. The dataset was recorded in an indoor scenario, using
six convergent cameras setup to produce multi-view videos, where each
video depicts a walking human. Each sequence contains at least 3 complete
gait cycles. The dataset contains videos of 20 walking persons with
a large variety of body size, who walk along straight and curved paths.
The multi-view videos have been processed to produce foreground silhouettes.
To validate our dataset, we have extended some appearance-based
2D gait recognition methods to work with 3D data, obtaining very encouraging
results. The dataset, as well as camera calibration information,
is freely available for research purpose
Multi-view gait recognition on curved
Appearance changes due to viewing angle changes cause difficulties for most of the gait recognition methods. In this paper, we propose a new approach for multi-view recognition, which allows to recognize people walking on curved paths. The recognition is based on 3D angular analysis of the movement of the walking human. A coarse-to-fine gait signature represents local variations on the angular measurements along time. A Support Vector Machine is used for classifying, and a sliding temporal window for majority vote policy is used to smooth and reinforce the classification results. The proposed approach has been experimentally validated on the publicly available “Kyushu University 4D Gait Database”
Entropy Volumes for Viewpoint Independent Gait Recognition
Gait as biometrics has been widely used for
human identi cation. However, direction changes cause
di culties for most of the gait recognition systems, due
to appearance changes. This study presents an e cient
multi-view gait recognition method that allows curved
trajectories on completely unconstrained paths for in-
door environments. Our method is based on volumet-
ric reconstructions of humans, aligned along their way.
A new gait descriptor, termed as Gait Entropy Vol-
ume (GEnV), is also proposed. GEnV focuses on cap-
turing 3D dynamical information of walking humans
through the concept of entropy. Our approach does
not require the sequence to be split into gait cycles.
A GEnV based signature is computed on the basis of
the previous 3D gait volumes. Each signature is clas-
si ed by a Support Vector Machine, and a majority
voting policy is used to smooth and reinforce the clas-
si cations results. The proposed approach is experimen-
tally validated on the \AVA Multi-View Gait Dataset
(AVAMVG)" and on the \Kyushu University 4D Gait
Database (KY4D)". The results show that this new ap-
proach achieves promising results in the problem of gait
recognition on unconstrained paths
Stereo Pictorial Structure for 2D Articulated Human Pose Estimation
In this paper, we consider the problem of 2D human
pose estimation on stereo image pairs. In particular,
we aim at estimating the location, orientation and scale of
upper-body parts of people detected in stereo image pairs
from realistic stereo videos that can be found in the Internet.
To address this task, we propose a novel pictorial structure
model to exploit the stereo information included in such
stereo image pairs: the Stereo Pictorial Structure (SPS). To
validate our proposed model, we contribute a new annotated
dataset of stereo image pairs, the Stereo Human Pose Estimation
Dataset (SHPED), obtained from YouTube stereoscopic
video sequences, depicting people in challenging poses
and diverse indoor and outdoor scenarios. The experimental
results on SHPED indicates that SPS improves on state-ofthe-
art monocular models thanks to the appropriate use of
the stereo informatio
Sistema digital de catalogación y consulta de documentos académicos: Tesis, Tesinas, Proyectos de Fin de Carrera
A digital system has been developed on order to catalogue and consult academic documents: Theses, First Degree Dissertations and Technical Degree Final Projects. The system uses a listing of bibliographical subjects which makes easy the catalogue and search of theses documents. The system guarantees the copyright because the document can be consulted, but they can not be printed or copied on external devices. In addition, a cataloguing and search protocol is proposed in order to the system can be correctly used. This system is available to be integrated in the Web information system of the Library of Córdoba University.Se ha desarrollado un sistema digital de catalogación y consulta de documentos académicos: Tesis, Tesinas y Proyectos de fin de carrera. El sistema incorpora un listado de materias bibliográficas que facilitan la catalogación y búsqueda de los documentos. El sistema garantiza la propiedad intelectual de los autores, porque permite que los documentos sean consultados, pero impiden que sean impresos o copiados en dispositivos externos. Además, se propone un protocolo de catalogación y consulta de estos documentos académicos para que el sistema pueda ser correctamente utilizado. Este sistema está disponible para ser integrado en la página Web de la Biblioteca de la Universidad de Córdoba
A new approach for multi-view gait recognition on unconstrained paths
Direction changes cause di culties for most of the gait recognition systems, due to appearance
changes. We propose a new approach for multi-view gait recognition, which
focuses on recognizing people walking on unconstrained (curved and straight) paths. To
this e ect, we present a new rotation invariant gait descriptor which is based on 3D
angular analysis of the movement of the subject. Our method does not require the sequence
to be split into gait cycles, and is able to provide a response before processing the
whole sequence. A Support Vector Machine is used for classifying, and a sliding temporal
window with majority vote policy is used to reinforce the classi cation results. The proposed
approach has been experimentally validated on \AVA Multi-View Dataset" and
\Kyushu University 4D Gait Database" and compared with related state-of-art work.
Experimental results demonstrate the e ectiveness of this approach in the problem of
gait recognition on unconstrained path
A new thresholding approach for automatic generation of polygonal approximations
The present paper proposes a new algorithm for automatic generation of
polygonal approximations of 2D closed contours based on a new thresholding
method. The new proposal computes the signi cance level of the contour
points using a new symmetric version of the well-known Ramer, Douglas -
Peucker method, and then a new Adaptive method is applied to threshold
the normalized signi cance level of the contour points to generate the polygonal
approximation. The experiments have shown that the new algorithm
has good performance for generating polygonal approximations of 2D closed
contours. Futhermore, the new algorithm does not require any parameter to
be tuned