Our Cofounder/CTO Henry Zhong holds a PhD in Computer Vision and Ubiquitous Computing, completed in 2017. His thesis is titled Lightweight Algorithms for Depth Sensor Equipped Embedded Devices. This post is aimed at providing a short overview of his PhD work. His full thesis and conference papers is available to read for free at ResearchGate.
The PhD research project was in the application of depth sensors to Ubiquitous Computing. Ubiquitous Computing envisions a world where computing is made to appear anytime and everywhere. It is core to Internet of Things (IoT) and wearable technologies.
Depth sensors are now found in tablets, smartphones and web cameras. Henry's research answers the following question: What kinds of applications can take advantage of depth sensors; and what algorithms can be developed to implement such applications?
Henry researched tasks that could be improved using depth sensors. From there, he created computer vision and machine learning algorithms to achieve these improvements and collected data to test solutions he had built. Algorithms were implemented in C# and C++.
This research resulted in the creation of three algorithms related to object detection, action recognition, and biometric identification: QuickFind, WashInDepth, and VeinDeep. These algorithms were found to exceed the performance of existing state-of-the-art methods. More details on these algorithms will be given in future posts.