A better understanding of pedestrian behavior is needed to enhance existing pedestrian simulation models. A study was conducted on microscopic pedestrian behavior during several interactions, with pedestrian walking speed and gait parameters (step frequency and length) as variables. Pedestrian trajectories at a signalized intersection in Vancouver, British Columbia, Canada, were extracted from video recordings by means of computer vision techniques. Walking speed and gait parameters were estimated by analyzing pedestrian speed profiles. The study provided detailed analysis of seven interactions. The variations in walking speed and gait parameter values across group size and gender during the seven interactions were also investigated. Results showed that, for some of the studied interactions, pedestrian speed alone may not be adequate to describe pedestrian behavior and that gait parameters can help to provide better understanding of pedestrian behavior in these particular interactions. Furthermore, a specific set of parameters was identified that can be extracted from the results and can be used to calibrate a microscopic pedestrian behavior-modeling platform currently being developed.