Objective
Humans have the impressive ability to recognize even noisy or blurred objects in scenes by using global context information. For instance, we expect the grayish blob in the image to be a car rather than a wild animal when the image has been taken in the streets of a metropolitan area. The importance of context information for humans has also been proven through psychophysical experiments. Due to its applicability for content-based image or video retrieval, research in computational image understanding, i.e. the automatic description of scene class, objects in the scene, and object and scene interrelations, has recently gained increased attention. Up to now, these different recognition tasks have mainly been treated separately.
However, the findings from psychophysics suggest that the combination of scene and object recognition will be also beneficial for computational scene description. The goal of this research project is to develop a computer vision system for combined scene classification and object categorization. The idea is to combine bottom-up knowledge, e.g. from low-level features, with top-down knowledge, e.g. information about the scene class, in an iterative manner. The hypothesis is that object classification accuracies will improve due to the use of scene context, even if the information from low-level features is of low quality.
The combination can be achieved best using statistical methods. Statistical models have been shown to be well suited for both scene and object recognition approaches. The project aims for improving upon state of the art by a statistical approach for combined scene and object recognition.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences artificial intelligence computer vision object detection
- natural sciences mathematics applied mathematics statistics and probability
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
FP6-2002-MOBILITY-5
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Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Coordinator
United Kingdom
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.