Universal Gestures for Human Robot Interaction (GESTIBOT): Difference between revisions

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Work framed by the Humanoids Robotics Research Area of the ISR Computer and Robot Vision Lab (Vislab).
This work is framed in the Humanoid Robotics Research area of the Computer and Robot Vision Lab (Vislab), ISR/IST.


Keywords: Computer Vision, Human Robot Interaction.
Keywords: Computer Vision, Human Robot Interaction, Gesture Recognition, Shared Attention.


=== Objectives ===
=== Objectives ===


Exploit the knowledge about human attention studies to derive efficient pattern search mechanisms in object detection tasks. Application of the methods to a humanoid robot in order to interact with objects of interest in the scene with improves reaction times.
To develop vision based pattern recognition methods able of detecting some universal gestures with strong relevance for sharing attention between a Robot and a Human (e.g. waving, pointing, looking).


=== Description ===
=== Description ===


Current object detection technology exhaustively searches the images for patterns of interest. Although such brute-force approaches may present good performance in terms of successful detections, they are often too computationally demanding because require the scan of the full image, independently of the task they are engaged on. Humans instead allocate their attentional resources ("computational power") to the most promising parts of the visual field, according to their current expectations. They are, therefore, able to react faster, in average, to the environmental events. In this work we will exploit the knowledge of humans visual attention to design artificial vision algorithms more efficient that existing ones.
Interaction methods between robots and humans has been classically addressed by using speech communication or predefined gestures, usually designed in an ad-hoc manner for expert users, i.e. users have to learn the association between the gestures and the meaning. However, more and more robots are aimed at being deployed in social and public environments, having to interact with non-expert users. In such cases, only universal gestures may be of relevance to consider. For instance, waving is interpreted in all societies as an attention trigger or an alerting mechanism. Also pointing (or looking) at a certain direction immediately drives the attention of the observer to the pointed (or looked at) direction. In this work we aim at implementing the skills in a humanoid robot to detect and produce gestures that convey implicit information to-from the user.
 
Beyond robotics, the developed methods will also have an important impact in future interactive systems, e.g. a digital camera can focus on the waving person, and likely lead to commercial applications.


=== Prerequisites ===
=== Prerequisites ===
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=== Expected Results ===
=== Expected Results ===


The algorithms will be implemented in the iCub robot platform. It is expected that the algorithms will allow faster reaction times and higher responsiveness to the external events that currently existing methodologies.  
The developed algorithms will be implemented in the humanoid robotic platform iCub. In the end of the project it is expected to illustrate the work done through a demonstration where:
The developed algorithms will also have an impact on the implementation of object detection algorithms (e.g. faces) in low power processors such as the ones existing in digital cameras, mobile phones, etc, possibly leading to commercial applications.
1 - a person waves to the robot and attracts its attention (the robot looks at the person).
2 - the person looks or points at an object and the robot detects which is the object of interest.
3 - The robot looks and points to the same object.
 
Some required tools for this work (e.g. person and waving detection software) are available in the research group.  


=== Related Work ===
=== Related Work ===


Multimodal Saliency-Based Bottom-Up Attention A Framework for the Humanoid Robot iCub, Jonas Ruesch, Manuel Lopes, Alexandre Bernardino, Jonas Hornstein, José Santos-Victor, Rolf Pfeifer, 2008 IEEE International Conference on Robotics and Automation Pasadena, CA, USA, May 19-23, 2008.
Waving detection using the local temporal consistency of flow-based features for real-time applications, Plinio Moreno, Alexandre Bernardino, and José Santos-Victor. Accepted at ICIAR 2009.
Link: http://www.isr.ist.utl.pt/labs/vislab/publications/08-icra-attention.pdf

Revision as of 14:15, 27 April 2009

The humanoid Robot iCub
  • Orientador: Prof. Alexandre Bernardino
  • Co-Orientador: Prof. José Santos Victor
  • Acompanhante: Dr. Plinio Moreno


This work is framed in the Humanoid Robotics Research area of the Computer and Robot Vision Lab (Vislab), ISR/IST.

Keywords: Computer Vision, Human Robot Interaction, Gesture Recognition, Shared Attention.

Objectives

To develop vision based pattern recognition methods able of detecting some universal gestures with strong relevance for sharing attention between a Robot and a Human (e.g. waving, pointing, looking).

Description

Interaction methods between robots and humans has been classically addressed by using speech communication or predefined gestures, usually designed in an ad-hoc manner for expert users, i.e. users have to learn the association between the gestures and the meaning. However, more and more robots are aimed at being deployed in social and public environments, having to interact with non-expert users. In such cases, only universal gestures may be of relevance to consider. For instance, waving is interpreted in all societies as an attention trigger or an alerting mechanism. Also pointing (or looking) at a certain direction immediately drives the attention of the observer to the pointed (or looked at) direction. In this work we aim at implementing the skills in a humanoid robot to detect and produce gestures that convey implicit information to-from the user.

Beyond robotics, the developed methods will also have an important impact in future interactive systems, e.g. a digital camera can focus on the waving person, and likely lead to commercial applications.

Prerequisites

Average grade > 14. It is recommended a good knowledge of Signal and/or Image Processing, as well as Machine Learning.

Expected Results

The developed algorithms will be implemented in the humanoid robotic platform iCub. In the end of the project it is expected to illustrate the work done through a demonstration where: 1 - a person waves to the robot and attracts its attention (the robot looks at the person). 2 - the person looks or points at an object and the robot detects which is the object of interest. 3 - The robot looks and points to the same object.

Some required tools for this work (e.g. person and waving detection software) are available in the research group.

Related Work

Waving detection using the local temporal consistency of flow-based features for real-time applications, Plinio Moreno, Alexandre Bernardino, and José Santos-Victor. Accepted at ICIAR 2009.