Congratulations to Zhiruo Zhou for passing her defense on September 25, 2023. Zhiruo’s thesis
is titled “Green Unsupervised Single Object Tracking: Technologies and Performance
Evaluation.” Her Dissertation Committee includes Jay Kuo (Chair), Antonio Ortega, and Stefanos
Nikolaidis (Outside Member). Zhiruo received several questions and suggestions from the
Committee members. Zhiruo answered the questions professionally.
Congratulations to Zhiruo for this milestone moment in life. MCL News team invited Zhiruo for a
short talk on her thesis and PhD experience, and here is the summary. We thank Zhiruo for her
kind sharing, and wish her all the best in the next journey.
“Video object tracking is one of the fundamental problems in computer vision and has diverse
real-world applications such as video surveillance and robotic vision. Given the ground-truth
bounding box of the object in the first frame of a test video, a single object tracker (SOT)
predicts the object box in all subsequent frames. Supervised trackers trained on labeled data
dominate the single object tracking field for superior tracking accuracy. The labeling cost and
the huge computational complexity hinder their applications on edge devices. Unsupervised
learning methods have also been investigated to reduce the labeling cost, but their complexity
remains high.
In my dissertation, I investigate the feasibility of lightweight high-performance tracking with
algorithmic transparency and no offline pre-training. I present our design of the green object
tracker that exploits spatial and temporal correlations at different granularities for more robust
tracking. It has been examined on a variety of benchmarks against recent state-of-the-arts, with
the inference complexity that is between 0.1%-10% of neural-network-based trackers. The
tracker is called ‘green’ due to its low computational complexity in both training and inference
stages, leading to a low carbon footprint and the ease of deployment on resource-limited
I would like to express my sincere gratitude to my supervisor, Professor C.-C. Jay Kuo, who
supports me with the invaluable advice and patience and sets the exemplar of a researcher for
me. I would also like to thank Professor Antonio Ortega, Professor Stefanos Nikolaidis and Dr.
Suya You for their help and advice on my thesis. Many thanks to all Media Communications Lab
members and alumnus who offered their kind help and company along the PhD journey. PhD is
an interesting yet challenging opportunity for one to exploring things that have never been
touched in the world. The process is strenuous but rewarding, and you will be well trained in
terms of both the academic thinking but also being a good team player. I wish everyone good
luck with their PhD journey, and I look forward to hearing about great news on green learning in
the future!”