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Tom Wilson, Vice President of Business Development at CogniVue, presents the "Efficiently Computing Disparity Maps for Low-Cost 3D Stereo Vision" tutorial within the "Front-End Image Processing for Vision Applications" technical session at the October 2013 Embedded Vision Summit East.

The ability to detect and determine the position of objects in 3D is important for many vision applications, such as gesture recognition, automotive safety and augmented reality. Various sensor technologies can be used to provide 3D images, with stereo vision being the best established approach. Disparity map generation is a particularly important part of stereo vision processing, and is very demanding in terms of processor performance, creating challenges for cost- and power-constrained systems. This presentation describes disparity map generation and why it is challenging. It also presents approaches to reduce the computational load if disparity map generation and present an example embedded implementation.

Here you’ll find a wealth of practical technical insights and expert advice to help you bring AI and visual intelligence into your products without flying blind.

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