@inproceedings{7bb2f02c9db1481aac4abf86e6797fbf,
title = "Efficient depth localization of objects in a 3D space using computational integral imaging",
abstract = "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{\textquoteright} bounding boxes, and by a straightforward blur measure analysis, we estimate the objects{\textquoteright} depth locations.",
keywords = "3D imaging, 3D object localization, computational integral imaging, depth localization",
author = "Michael Kadosh and Anton Fraiman and Eli Peli and Yitzhak Yitzhaky",
note = "Publisher Copyright: {\textcopyright} 2023 SPIE. All rights reserved.; Artificial Intelligence for Security and Defence Applications 2023 ; Conference date: 04-09-2023 Through 05-09-2023",
year = "2023",
month = jan,
day = "1",
doi = "10.1117/12.2683627",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Henri Bouma and Judith Dijk and Radhakrishna Prabhu and Stokes, {Robert J.} and Yitzhak Yitzhaky",
booktitle = "Artificial Intelligence for Security and Defence Applications",
address = "United States",
}