Visual recognition of driver hand-held cell phone use based on hidden CRF

In this paper, we propose an automatic system that recognizes driver's abnormal behavior, i.e. cell phone use. Driver's actions are captured using a camera mounted above the dash board. Then the observed features are input into a Hidden Conditional Random Fields (HCRF) model. To incorporate long range dependencies, features are collected within a local window from neighbor sites. We evaluate the presented algorithm on the real video segments, and the results show that the system can successfully recognize the behavior.