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An HMM Approach with Inherent Model Selection for Sign Language and Gesture Recognition

Related publications (33)

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On the Recognition Performance of BioHashing on state-of-the-art Face Recognition models

Sébastien Marcel, Hatef Otroshi Shahreza

Face recognition has become a popular authentication tool in recent years. Modern state-of-the-art (SOTA) face recognition methods rely on deep neural networks, which extract discriminative features from face images. Although these methods have high recogn ...

IEEE2021

Data-Driven Movement Subunit Extraction from Skeleton Information for Modeling Signs and Gestures

Marzieh Razavi, Sandrine Tornay

Sequence modeling for signs and gestures is an open research problem. In thatdirection, there is a sustained effort towards modeling signs and gestures as a se-quence of subunits. In this paper, we develop a novel approach to infer movementsubunits in a da ...

Idiap2019

Tree-structured Classifier for Acceleration-based Activity and Gesture Recognition on Smartwatches

Karl Aberer, Julien Eberle, Dipanjan Chakraborty

This paper proposes a new method for recognizing both activities and gestures by using acceleration data collected on a smartwatch. While both activity recognition techniques and gesture recognition techniques employ acceleration data, these techniques are ...

Ieee2016

Dynamic Classifier Fusion for Multi-sensory Activity Recognition

Hesam Sagha

Nowadays, many systems rely on fusing different sources of information to recognize human activities and gestures, speech, or brain activities for applications in areas such as clinical practice, and health care and Human Computer Interaction (HCI). Typica ...

EPFL2013

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We propose a method to automatically translate a pre-existing activity recognition system, devised for a source sensor domain S, so that it can operate on a newly discovered target sensor domain T , possibly of different modality. First, we use MIMO system ...

2012

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Gesture recognition is becoming a popular way of interaction, but still suffers of important drawbacks to be integrated in everyday life devices. One of these drawbacks is the activation of the recognition system – trigger gesture - which is generally tiri ...

2011

Max-pooling convolutional neural networks for vision-based hand gesture recognition

Automatic recognition of gestures using computer vision is important for many real-world applications such as sign language recognition and human-robot interaction (HRI). Our goal is a real-time hand gesture-based HRI interface for mobile robots. We use a ...

2011

The work described in this thesis takes place in the context of capturing real-life audio for the analysis of spontaneous social interactions. Towards this goal, we wish to capture conversational and ambient sounds using portable audio recorders. Analysis ...

EPFL2011

Privacy-Sensitive Audio Features for Conversational Speech Processing

Sree Hari Krishnan Parthasarathi

Ecole Polytechnique Fédérale de Lausanne2011

On the use of brain decoded signals for online user adaptive gesture recognition systems

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Andrea Biasiucci, Daniel Roggen

Activity and context recognition in pervasive and wearable computing ought to continuously adapt to changes typical of open-ended scenarios, such as changing users, sensor characteristics, user expectations, or user motor patterns due to learning or aging. ...

2010