Activity Recognition from Trajectory Data

PhD Qualifying Examination


Title: "Activity Recognition from Trajectory Data"

by

Mr. Yin ZHU


Abstract:

In today’s world, we have increasingly sophisticated means to record the 
movement of humans and other moving objects in the form of trajectory data. 
These data are being accumulated at an extremely fast rate. As a result, 
knowledge dis- covery from these data for recognizing activities has become an 
important problem. The discovered activity patterns can help us understand 
people’s lives, analyze traf- fic in a large city and study social networks 
among people. Trajectory-based activ- ity recognition builds upon some 
fundamental functions of location estimation and machine learning, and can 
provide new insights on how to infer high-level goals and objectives from 
low-level sensor readings. In this report, we survey the area of 
trajectory-based activity recognition. We start from research in location 
estimation from sensors for obtaining the trajectories. We then review 
trajectory-based activ- ity recognition research. We classify the research work 
on trajectory-based activity recognition into several broad categories, and 
systematically summarize existing work as well as future works in light of the 
categorization.


Date:                   Wednesday, 9 November 2011

Time:                   10:00am - 12:00noon

Venue:                  Room 3405
                         lifts 17/18

Committee Members:	Prof. Qiang Yang (Supervisor)
                         Prof. Dik-Lun Lee (Chairperson)
 			Dr. Lei Chen
 			Dr. Raymond Wong


**** ALL are Welcome ****