Master thesis Computer Science: Object movement modeling

This thesis develops a flexible customer behavior analysis system, including essential head pose estimation or F-formation modules. This system will be evaluated in an actual retail store. Further, after studying the system, realizing the mentioned problems of the head pose problem, we also propose a process to collect the head pose dataset and multi-task deep neural network model, fusing face detection and head pose estimation to yield face position and head pose at the same time.
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Master thesis Computer Science: Object movement modeling VIETNAM NATIONAL UNIVERSITY, HANOIUNIVERSITY OF ENGINEERING AND TECHNOLOGY NGUYEN DINH TUANOBJECT MOVEMENT MODELING Master thesis Major: Computer Science Ha Noi - 2021 VIETNAM NATIONAL UNIVERSITY, HANOI UNIVERSITY OF ENGINEERING AND TECHNOLOGY NGUYEN DINH TUAN OBJECT MOVEMENT MODELING Major: Computer ScienceSupervisor: Dr. Tran Quoc Long HA NOI - 2021ABSTRACT Artificial intelligence has advanced in recent years, enabling the development of numer-ous applications for seeing the physical world and assisting humans with a variety of activities.Among the numerous applications of video understanding problems, one of the more challeng-ing branches is object movement analysis. To understand object movement, we must rely onthe context of the activity to indicate the object’s states, such as shopping, going to the hospital,participating in sports, or crowd behavior. Despite the amount of studies, the majority of studiesfocus on specific behaviors, and there is currently no comprehensive model for this topic. This thesis establishes a framework for modeling object movement in the setting of cus-tomers in a retail store. To be more precise, we begin by modeling the store’s consumers’individual and group behavior. Second, we design and implement this modeling using a dis-tributed approach, which enables efficient deployment of the system. Finally, we installed andassessed this system in a physical store in Vietnam. After conducting experiments with the system, we discovered that head pose estimation isa significant module in the consumer behavior analysis problem. However, models that performwell on benchmark datasets do not always perform well when deployed. This occurs as a resultof the data collecting system’s complex architecture. After all, current benchmark datasets aregenerated only in a laboratory setting. As a result, this thesis also provides a novel techniquethat requires a dataset, an easy-to-set-up and gather system, in order to obtain more diverse data.Additionally, we propose multi-task model learning for face detection and head pose estimationsimultaneously, which reduces latency in comparison to the traditional method for head poseestimation, which relies on face detection and head pose estimation independently. iACKNOWLEDGMENTS There are many people I must thank for contributing to the two wonderful years of myexperience as a Master student. First I want to express my gratitude to my adviser, Dr. Tran Quoc Long for continu-ous support of my study and research, for his patience, motivation, enthusiasm, and immenseknowledge. His advice was invaluable to me during my student and master’s years. He has pro-vided me with numerous opportunities to participate in a variety of projects, both productionand research, through which I have learned many fundamental and significant lessons. He ex-tracted the essence of my idea, uncovered the more fundamental story, and placed it in a largercontext when I pitched it to him. He gives me advise and helps me see things more clearly whenI’m in trouble. I am very grateful to Dr. Long for not only educating me about computer visionor the art of communication, but also for teaching me how to think. I’ve been very fortunate to learn from many other incredibly amazing people in MEMSLAB (Micro Electronic Mechanical System Lab), leaded by Prof. Chu Duc Trinh, they alwaysgive me a chance, insightful remarks, feedback and guidance. I would like to thank my closecollaborator, MSc. Phan Hoang Anh who I’ve had the distinct pleasure of working with andlearning from through robotics project and thoughtful discussions. He is very wonderful andmotivating leader, who always knows how to lift his team from trouble and push the project tomilestone. I also have to thank Assoc. Prof. Le Thanh Ha, who’ve directed Human Machine In-teraction (HMI) laboratory, where I have participated for more than three years since I was afreshman. Assoc. Prof. Le Thanh Ha , Dr. Nguyen Chi Thanh, Dr. Nguyen Do Van, Assoc.Prof. Nguyen Thi Thuy and member of HMI Lab enthusiastically shared their experience andprovided feedback on my computer vision project. I’d like to thank Mr. Nguyen Viet Hung, aformer member of HMI Lab, for introducing me to the lab during this time. He was the first per-son to introduce me about the field of research and always encouraged me to learn new things.I also appreciate duration of four years he was my room mate, he is like my brother to me. I have to thank many people who have contributed to my daily life and who have mademy experience at University of Eng ...