News

Press release 12/1/18 – Improve sound experience and safety at large, cultural events in the city

Press release 12/1/18   Management of Networked IoT Wearables – Very Large Scale Demonstration of Cultural and Security Applications Improve sound experience and safety at large, cultural events in the city The innovation project MONICA will demonstrate how cities can use the Internet of Things to deal with sound, noise and security challenges at big, cultural, open-air events. A range of applications will be demonstrated in six major European cities involving more than 100.000 users in total. Imagine sound zones…

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RESEARCH – CREATE – INNOVATE

The Single RTDI State Aid Action “RESEARCH – CREATE – INNOVATE” support measure is funded by the Operational Programme Competitiveness, Entrepreneurship and Innovation 2014-2020 (EPAnEK). The measure aims to support research and innovation, technological development and demonstration at operating enterprises for the development of new or improved products, the development of synergies among enterprises, research and development centres and higher education sector as well as to support the patentability of research results and industrial property. In that context, the main objectives of…

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Best Paper Award ICBHI 2017

This work presented a fall detection method based on Recurrent Neural Networks. It leverages the ability of recurrent networks to process sequential data, such as acceleration measurements from body-worn devices, as well as data augmentation in the form of random rotations of the input acceleration signal. Τhe proposed method was able to find all but one fall event, while at the same time producing no false alarms when tested on the publicly available URFD dataset. Proceedings/Precision Medicine Powered by pHealth…

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The Visual Computing Lab of CERTH-ITI, participated in the IEEE International Conference on Computer Vision (ICCV) 2017

The Visual Computing Lab of CERTH-ITI, participated in the IEEE International Conference on Computer Vision (ICCV) 2017, held between 22-29 October, in Venice, Italy. The conference, being the major international computer vision event, had an exciting programme of 621 papers, presenting the latest advances in the field. This year, the attendance of ICCV increased by 113%, having 3107 attendees! Our presented work was a poster paper, entitled “Non-linear Convolution Filters for CNN-based Learning”, by G. Zoumpourlis, A. Doumanoglou, N. Vretos…

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Deep Affordance-grounded Sensorimotor Object Recognition CVPR 2017 HONOLULU

S. Thermos, G. T. Papadopoulos, P. Daras, G. Potamianos, “Deep Affordance-grounded Sensorimotor Object Recognition”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017), Honolulu, Hawaii, USA, July 2017. Abstract: It is well-established by cognitive neuroscience that human perception of objects constitutes a complex process, where object appearance information is combined with evidence about the so-called object “affordances”, namely the types of actions that humans typically perform when interacting with them. This fact has recently motivated the “sensorimotor” approach to…

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Volterra-based convolution filter implementation in Torch

Download the layer’s code from here: VolterraConvolution.zip The code is based on the following publication: G. Zoumpourlis, A. Doumanoglou, N. Vretos, P. Daras, “Non-linear Convolution Filters for CNN-based Learning”, IEEE International Conference on Computer Vision (ICCV 2017), Venice, Italy, October 22-29 2017

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FORENSOR: Action Recognition

Action Recognition via Motion Analysis In this method, the first step of performing real-time object tracking is based on background subtraction. Initially, the algorithm grabs an image of the background, assuming that the frame is empty of subjects. Subsequently, while capturing each new frame, the background is subtracted by the newly acquired image and the resulted outcome is thresholded to form a foreground binary mask. This mask is further enhanced by the morphological operation of dilation and finally a connected…

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Factory2Fit – Developing the Factories of the Future

The Factory2Fit Project By developing solutions to make the factory environment more flexible and adaptable, the Factory2Fit project will bring increased worker motivation, satisfaction and productivity. It will help current and future workers to become knowledge workers in smart factories with fulfilling careers. The Factory2Fit Idea The core idea behind the Factory2Fit project is that the workers are experts in their own work – therefore they should have an active role in designing their work. The adaptation solutions that Factory2Fit will deliver are based on a…

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Visual Computing Lab

The focus of the Visual Computing Laboratory is to develop new algorithms and architectures for applications in the areas of 3D processing, image/video processing, computer vision, pattern recognition, bioinformatics and medical imaging.

Contact Information

Dr. Petros Daras, Principal Researcher Grade Α
1st km Thermi – Panorama, 57001, Thessaloniki, Greece
P.O.Box: 60361
Tel.: +30 2310 464160 (ext. 156)
Fax: +30 2310 464164
Email: daras@iti.gr