Images and depth for high resolution, low-latency sensing and security applications

The thesis focuses on using images and depths for high resolution, low latency sensing, and then using these sensing techniques to build security applications. First, we introduce the usefulness of high quality depth sensing, and the difficulty to acquire such depth stream via pure hardware approach. Then, we propose our sensor fusion approach, which combines depth camera and color camera. Chapter 2 puts forward a low cost approach to use a high spatial resolution color stream to help aggressively increase the spatial resolution of the depth stream. Continuing this direction, Chapter 3 proposes to use optical ow to forward warp the depth stream according to a high frequency, low latency CMOS color stream. The warping can create a high frequency, low latency depth stream. In both Chapter 2 and Chapter 3, we show that the improved depth sensing can benefit lots of applications. In Chapter 4, we propose a SafetyNet, which can reliably detecting and rejecting adversarial examples. With the revolutionary SafetyNet architecture and the advanced depth sensing, we can reliably prove to users whether a picture of a scene is real or not. In sum, the thesis focuses on improving sensing technologies and building vision and security applications around the sensing technologies.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Computer Science

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2019

Author dc:creator

• Lu, Jiajun

Contributors dc:contributor

• Forsyth, David
• Hoiem, Derek
• Lazebnik, Svetlana
• Wilson, Andy

• depth
• resolution
• latency
• security

Statement dc:rights

• Copyright 2018 Jiajun Lu

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/102476

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/102476