Accurate localization and recognition of objects in the three dimensional (3D) space can be useful in security and defence applications such as scene monitoring and surveillance. A main challenge in 3D object localization is to find the depth location of objects. We demonstrate here the use of a camera array with computational integral imaging to estimate depth locations of objects detected and classified in a two-dimensional (2D) image. Following an initial 2D object detection in the scene using a pre-trained deep learning model, a computational integral imaging is employed within the detected objects’ bounding boxes, and by a straightforward blur measure analysis, we estimate the objects’ depth locations.
Efficient depth localization of objects in a 3D space using computational integral imaging
Artificial Intelligence for Security and Defence Applications ; 2023 ; Amsterdam, Netherlands
Proc. SPIE ; 12742
2023-10-17
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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