LiDAR assisted large-scale privacy protection in street view cycloramas

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Abstract

The past decade has seen a rise in capturing public spaces for providing well-organized and geo-positioned databases of street view imagery. However, capturing public spaces is challenging, as they contain privacy-sensitive objects, such as faces and license plates. Therefore, these objects must be detected and blurred through an automated process. Although automated methods are labour-free, large resolution images incur high costs for processing. In this research, as we transition from 100 to 250-megapixel system (per cyclorama), we present a framework that reduces the search space of a detection algorithm using depth data obtained from a LIDAR scanner. After then increasing the resolution by 2.5 times and comparing several deep learning architectures, we manage to keep execution time at nearly the same time.
Original languageEnglish
Title of host publicationIS&T International Symposium on Electronic Imaging
Publication statusPublished - 2018
EventIS&T International Symposium on Electronic Imaging Science and Technology, : Image Processing: Algorithms and Systems XV - Burlingame, United States
Duration: 29 Jan 20172 Feb 2017

Conference

ConferenceIS&T International Symposium on Electronic Imaging Science and Technology,
CountryUnited States
CityBurlingame
Period29/01/172/02/17

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