Falls among the elderly are concerning, especially if they go unnoticed for an extended period of time. Due to fear of falling, many people end up in assisted living facilities or nursing homes which are costly and the lack of independence greatly affects quality of life. Finding ways to allow the elderly to safely stay in their own homes longer not only reduces cost of living and increases well-being, but also alleviates the families’ burden of worrying about their loved ones. Due to their low cost, cameras are a convenient option for monitoring. This study made use of this and developed an algorithm to be used with a single video camera in order to determine when someone has fallen or is about to fall, so an alarm could be set off to alert a caretaker for help. The developed algorithm was tested for a variety of scenarios including falling down stairs, partially occluding the subject, low light levels, and placing the camera at a variety of angles. The acceleration values obtained were also compared with an Inertial Measurement Unit. The algorithm successfully tracked the person and detected falls in each scenario. The comparison with the IMU sensor points toward further potential for clinical applications in fall risk assessment.