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Communication Dans Un Congrès Année : 2015

DAcImPro: A novel database of acquired image projections and its application to object recognition

Résumé

Projector-camera systems are designed to improve the projection qual- ity by comparing original images with their captured projections, which is usually complicated due to high photometric and geometric variations. Many research works address this problem using their own test data which makes it extremely difficult to compare different proposals. This paper has two main contributions. Firstly, we introduce a new database of image projections that, covering photo- metric and geometric conditions and providing data for ground-truth computa- tion, can serve to evaluate different algorithms in projector-camera systems. Sec- ondly, a new object recognition scenario from acquired projections is presented, which could be of a great interest in such domains, as home video projections and public presentations. We show that the task is more challenging than the classical recognition problem and thus requires additional pre-processing, such as color compensation or projection area selection
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Dates et versions

hal-01805040 , version 1 (01-06-2018)

Identifiants

  • HAL Id : hal-01805040 , version 1

Citer

Aleksandr Setkov, Fabio Martinez, Michèle Gouiffès, Christian Jacquemin, Maria Vanrell, et al.. DAcImPro: A novel database of acquired image projections and its application to object recognition. International Symposium on Visual Computing, Jan 2015, Las Vegas, United States. ⟨hal-01805040⟩
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