@inproceedings{ddc4bc65366c42c9b56b70b2ce6a3fb8,
title = "3D noise-resistant segmentation and tracking of unknown and occluded objects using integral imaging",
abstract = "Three dimensional (3D) object segmentation and tracking can be useful in various computer vision applications, such as: object surveillance for security uses, robot navigation, etc. We present a method for 3D multiple-object tracking using computational integral imaging, based on accurate 3D object segmentation. The method does not employ object detection by motion analysis in a video as conventionally performed (such as background subtraction or block matching). This means that the movement properties do not significantly affect the detection quality. The object detection is performed by analyzing static 3D image data obtained through computational integral imaging With regard to previous works that used integral imaging data in such a scenario, the proposed method performs the 3D tracking of objects without prior information about the objects in the scene, and it is found efficient under severe noise conditions.",
keywords = "Computational integral imaging, Three dimensional object tracking, Three dimensional segmentation",
author = "Doron Aloni and Jung, {Jae Hyun} and Yitzhak Yitzhaky",
note = "Publisher Copyright: {\textcopyright} COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.; Counterterrorism, Crime Fighting, Forensics, and Surveillance Technologies 2017 ; Conference date: 11-09-2017 Through 12-09-2017",
year = "2017",
month = jan,
day = "1",
doi = "10.1117/12.2278244",
language = "American English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Yitzhak Yitzhaky and Stokes, {Robert James} and Henri Bouma and Felicity Carlysle-Davies",
booktitle = "Counterterrorism, Crime Fighting, Forensics, and Surveillance Technologies",
address = "United States",
}