This paper presents a methodology that quantifies gait and fall characteristics from video of real-life fall events. The method consists in selecting on-screen the points on the ground where the feet are in contact with the ground. The essence of the method lies in establishing a transformation from the video frames to the “real world.” In projected images, geometric properties such as lengths, angles, and parallelism are not preserved; thus, concepts of projective geometry are applied, namely homography. Because the ground is an invariant plane, using this plane for homography results in a constant transformation. The homographic transformation relies on the accuracy in the selection of on-screen points. An optimization algorithm that minimizes the errors caused by inaccurate on-screen point selection improves the results of the homographic transformation. Experimental trials are conducted at three walking velocities (slow, preferred, and fast) using two video cameras and a GAITRite walkway system. Spatial parameters of two independent video analyses are compared with the GAITRite system, yielding a limit of agreement of step length from −2.12 cm to 2.03 cm. Temporal parameters are less confident due to the existence of dropped frames in the video footage. This method is then used to analyze two real fall events as demonstrative cases. First, the gait characteristics are analyzed before imbalance, and subsequently, the characteristics of stepping are analyzed during the fall. In particular, we propose the stepping/impact angle as the metric that quantifies how much stepping affected the direction of the fall.