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Abstract

A three-dimensional (3-D) machine-vision obstacle detection solution involving a method and apparatus for performing high-integrity, high efficiency machine vision. The machine vision obstacle detection solution converts two-dimensional video pixel data into 3-D point data that is used for calculation of the closest distance from the vehicle to points on the 3-D objects, for any object within view of at least one imaging device configured to provide obstacle detection. The obstacle detection apparatus includes an image acquisition device arranged to view a monitored scene stereoscopically and pass the resulting multiple video output signals to a computer for further processing. The multiple video output signals are connected to the input of a video processor adapted to accept the video signals. Video images from each camera are then synchronously sampled, captured, and stored in a memory associated with a general purpose processor. The digitized image in the form of pixel information can then be retrieved, manipulated and otherwise processed in accordance with capabilities of the vision system. The machine vision obstacle detection method and apparatus involves two phases of operation: training and run-time. Training is a series of steps in which 3-D image data and other 3-D data are combined into a 3-D model of a vehicle being navigated. During run-time, the entities observed and optionally segmented objects from a camera on the vehicle are compared against the model to detect obstacles and their relative position and trajectory.

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