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A Probabilistic Temporal Model for Joint Attribute Extraction and Behavior Recognition
Related publications (55)
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In this work, we present a simple biometric indexing scheme which is binning and retrieving cancelable deep face templates based on frequent binary patterns. The simplicity of the proposed approach makes it applicable to unprotected as well as protected, i ...
IEEE2022An HMM Approach with Inherent Model Selection for Sign Language and Gesture Recognition
HMMs have been the one of the first models to be applied for sign recognition and have become the baseline models due to their success in modeling sequential and multivariate data. Despite the extensive use of HMMs for sign recognition, determining the HMM ...
ACL2020Theoretical foundations of forward feature selection methods based on mutual information
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ELSEVIER SCIENCE BV2019Variational Methods for Human Modeling
A large part of computer vision research is devoted to building models
and algorithms aimed at understanding human appearance and behaviour
from images and videos. Ultimately, we want to build automated systems
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EPFL2018Tree-structured Classifier for Acceleration-based Activity and Gesture Recognition on Smartwatches
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Ieee2016Impact of Tone-mapping Algorithms on Subjective and Objective Face Recognition in HDR Images
Crowdsourcing is a popular tool for conducting subjective evaluations in uncontrolled environments and at low cost. In this paper, a crowdsourcing study is conducted to investigate the impact of High Dynamic Range (HDR) imaging on subjective face recogniti ...
2015Biometrics Evaluation Under Spoofing Attacks
Sébastien Marcel, André Anjos, Ivana Chingovska
While more accurate and reliable than ever, the trustworthiness of biometric verification systems is compromised by the emergence of spoofing attacks. Responding to this threat, numerous research publications address isolated spoofing detection, resulting ...
Ieee-Inst Electrical Electronics Engineers Inc2014Object Classification and Detection in High Dimensional Feature Space
Object classification and detection aim at recognizing and localizing objects in real-world images. They are fundamental computer vision problems and a prerequisite for full scene understanding. Their difficulty lies in the large number of possible object ...
Programme doctoral en Informatique, Communications et Information2013Sparse Binary Features for Image Classification
In this work a new method for automatic image classification is proposed. It relies on a compact representation of images using sets of sparse binary features. This work first evaluates the Fast Retina Keypoint binary descriptor and proposes imp ...
2013Inferring social activities with mobile sensor networks
While our daily activities usually involve interactions with others, the state-of-the-art methods on activity recognition do not exploit the relationship between social interactions and human activity. This paper addresses the problem of interpreting socia ...
2013