A few days of a robot's life in the human's world: toward incremental individual recognition

摘要

This thesis presents an integrated framework and implementation for Mertz, an expressive robotic creature for exploring the task of face recognition through natural interaction in an incremental and unsupervised fashion. The goal of this thesis is to advance toward a framework which would allow robots to incrementally get to know a set of familiar individuals in a natural and extendable way. This thesis is motivated by the increasingly popular goal of integrating robots in the home. In order to be effective in human-centric tasks, the robots must be able to not only recognize each family member, but also to learn about the roles of various people in the household. In this thesis, we focus on two particular limitations of the current technology. Firstly, most of face recognition research concentrate on the supervised classification problem. Currently, one of the biggest problems in face recognition is how to generalize the system to be able to recognize new test data that vary from the training data. Thus, until this problem is solved completely, the existing supervised approaches may require multiple manual introduction and labelling sessions to include training data with enough variations. Secondly, there is typically a large gap between research prototypes and commercial products, largely due to lack of robustness and scalability to different environmental settings. In this thesis, we propose an unsupervised approach which would allow for a more adaptive system which can incrementally update the training set with more recent data or new individuals over time. Moreover, it gives the robots a more natural social recognition mechanism to learn not only to recognize each person's appearance, but also to remember some relevant contextual information that the robot observed during previous interaction sessions. Therefore, this thesis focuses on integrating an unsupervised and incremental face recognition system within a physical robot which interfaces directly with humans through natural social interaction. The robot autonomously detects, tracks, and segments face images during these interactions and automatically generates a training set for its face recognition system. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.) (Abstract shortened by UMI.)