People tracking using synthetically generated depth maps

Modern 3D sensors using time-of-flight and structured light technology are increasingly being used in a number of interesting applications. One such application is people tracking where the available 3D information enables more robust human detection and tracking methods than those based on classic video cameras. A large data set is typically required both for testing and tuning of the solution. We describe a methodology for efficient development of 3D applications using synthetically generated depth maps to complement the available data set obtained with real cameras. To demonstrate the effectiveness of the approach, a case study in the area of people counting with 3D sensors is presented.