Spanish National Research Council · University of Seville
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Funding for the research activities carried out at IMSE-CNM comes primarily from the participation in competitive tender processes. The research is then conducted out via agreements, projects and contracts with national and international public organizations and private companies and organizations.



ENVISAGE
Enabling Vision Technologies for Integrated Intelligent Transportation
PI: Ricardo Carmona Galán
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Type: Research project
Reference: RTI2018-097088-B-C31
Funding Body: Ministerio de Ciencia, Innovación y Universidades
Start date: 01/01/2019
End date: 31/12/2021
Funding: 144.958,00 €
Abstract: The objective of this project is the development of embedded vision systems for intelligent transport. The aim is to capture the specificities of this field of application and incorporate them into a holistic design flow. In this way, we will develop embedded vision systems adapted for autonomous platforms and vehicles and to be incorporated to the traffic control and monitoring infrastructure. The main challenge will be the implementation of an important amount of computing power under a restricted power budget. The conventional approach, in which the different components are developed separately from specifications derived from a high-Ievel description, can be inefficient, leading to sub-optimal performance. Our approach consists of multi-parametric and multi-Ievel optimization.
We will develop a system description tool that will allow us to navigate the hierarchy of the vision system and propagate specifications and restrictions from the device- to the application-Ievel and vice versa.

ACHIEVE
Advanced Hardware/Software Components for Integrated/Embedded Vision Systems
PI: Ricardo Carmona Galán web
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Type: Research project
Reference: 765866
Funding Body: European Union
Start date: 01/10/2017
End date: 30/09/2021
Funding: 2.230.856,64 €
Abstract: ACHIEVE-ETN aims at training a new generation of scientists through a research programme on highly integrated hardware-software components for the implementation of ultra-efficient embedded vision systems as the basis for innovative distributed vision applications. They will develop core skills in multiple disciplines, from image sensor design to distributed vision algorithms, and at the same time they will share the multidisciplinary background that is necessary to understand complex problems in information-intensive vision-enabled aplliccations. Concurrently, they will develop a set of transferable skills to promote their ability to cast their research results into new products and services, as well as to boost their career solutions for emerging technology markets in Europe and worldwide but also to drive new businesses through engaging in related entrepreneurial activities. The consortium is composed of 6 academic and 1 insdustrial beneficiaries and 4 industrial partners. The training of the 9 ESRs will be achieved by the proper combination of excellent research, secondments with industry, specific courses on core and transferable skills, and academic-industrial workshops and networking events, all in compliance with the call´s objectives of international, intersectoral and interdisciplinary mobility.

iCAVEATS
Integrated components and architectures for embedded vision in transportation and security applications
PI: Ricardo Carmona Galán web
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Type: Research project
Reference: TEC2015-66878-C3-1-R
Funding Body: Ministerio de Economía y Competitividad
Start date: 01/01/2016
End date: 31/12/2018
Funding: 197.714,00 €
Abstract: This project aims to the capitalization of the acquired know-how by developing a library of hardware components and architectures. They have to be compatible with OpenVX descriptions and aimed to reduce power consumption of mainly-software implementations. We will include low and medium-level processing blocks, new sensor abilities, like photon counting and time-of-flight estimation, and aspects more related to the system level, like energy management and interfacing with other signal processing chips. We will explore technological alternatives that may provide a more efficient implementation of OpenVX functions. These modifications will be transparent from the point of view of the application developer and the designer of computer vision algorithms.
In order to demonstrate the validity of the approach we will build a vision system on-a-chip for intelligent transportation and security applications. We will develop demonstrators to properly expose the potential of this approach to embedded vision.