Objective
In many application domains all over the world there is a trend from “single-view imaging” towards “multi-view imaging”. Some examples are the introduction of 3D/4D imaging in Healthcare, High Definition TV and beyond in Broadcasting, multiple connected Surveillance Cameras for monitoring a scene. These applications have in common that they all involve an explosive growth in the generation of images and the need for real time handling of images and data. The question arises how to deal with this growth of complexity.
Breakthrough technologies are needed to make imaging applications, such as the ones described above, handle the more and more demanding requirements concerning image quality and reliability and speed of image analysis:
• Image acquisition needs to become much more intelligent about what data to acquire
• Multi-view video processing requires sophisticated inter-camera calibration tools and sophisticated algorithms
• Acquisition devices will also need to become more context-aware: devices should be aware of the existence of other cameras.
Project Objectives
PANORAMA will provide autonomous image acquisition, tightly coupled to the image sensor by research, development and demonstrating generic breakthrough technologies and hardware architectures for a broad range of imaging applications. Object segmentation is a basic building block of many intermediate and low level image analysis methods. It will be used in an X-ray system to locate anatomical regions of interest. In broadcast applications, it can find people’s faces and optimize Image Quality. In a multi-camera setup these imaging parameters will be optimized to provide a consistent display of faces.
On completion PANORAMA will deliver solutions for applications in medical imaging, broadcasting systems and security & surveillance, all of which face similar challenging issues in the real time handling and processing of large volumes of image data.
Fields of science
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
Topic(s)
Call for proposal
ENIAC-2011-1
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Coordinator
5684 PC Best
Netherlands
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Participants (16)
4827 HG BREDA
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5612 AE Eindhoven
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4181AE Waardenburg
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2803 WV Gouda
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9410 AD Beilen
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92150 SURESNES
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75272 Paris
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42570 SAINT HEAND
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78153 Le Chesnay Cedex
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LS2 9JT Leeds
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BT9 5DJ Belfast
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9050 GENT
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2600 ANTWERPEN
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20864 Agrate Brianza
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95131 Catania
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