LiDAR-assisted large-scale privacy protection in street-view cycloramas

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

1 Citation (Scopus)
10 Downloads (Pure)

Abstract

Recently, privacy has a growing importance in several domains, especially in street-view images. The conventional way to achieve this is to automatically detect and blur sensitive information from these images. However, the processing cost of blurring increases with the ever growing resolution of images. We propose a system that is cost-effective even after increasing the resolution by a factor of 2.5. The new system utilizes depth data obtained from LiDAR to significantly reduce the search space for detection, thereby reducing the processing cost. Besides this, we test several detectors after reducing the detection space and provide an alternative solution based on state-of-the-art deep learning detectors to the existing HoG-SVM-Deep system that is faster and has a higher performance.

Original languageEnglish
Title of host publication17th Image Processing: Algorithms and Systems Conference, IPAS 2019
Number of pages6
DOIs
Publication statusPublished - 13 Jan 2019
Event17th Image Processing: Algorithms and Systems Conference, IPAS 2019 - Burlingame, United States
Duration: 13 Jan 201917 Jan 2019

Conference

Conference17th Image Processing: Algorithms and Systems Conference, IPAS 2019
CountryUnited States
CityBurlingame
Period13/01/1917/01/19

Fingerprint

Dive into the research topics of 'LiDAR-assisted large-scale privacy protection in street-view cycloramas'. Together they form a unique fingerprint.

Cite this