PT Unknown
AU Aleksandr Setkov
   Fabio Martinez Carillo
   Michele Gouiffes
   Christian Jacquemin
   Maria Vanrell
   Ramon Baldrich
TI DAcImPro: A Novel Database of Acquired Image Projections and Its Application to Object Recognition
BT Advances in Visual Computing. Proceedings of 11th International Symposium, ISVC 2015 Part II
PY 2015
BP 463
EP 473
VL 9475
DI 10.1007/978-3-319-27863-6_43
DE Projector-camera systems; Feature descriptors; Object recognition
AB Projector-camera systems are designed to improve the projection quality 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 acquired image projections (DAcImPro) that, covering photometric and geometric conditions and providing data for ground-truth computation, can serve to evaluate different algorithms in projector-camera systems. Secondly, 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.
ER