Determining Depth from Structured Light Using Trained Classifiers

• Main Authors: Tankovich Vladimir, Rhemann Christoph, Fanello Sean Ryan Francesco, KIM David, Izadi Shahram, Kowdle Adarsh Prakash Murthy
• Format: Patent
• Language: English
• Published: 17.08.2017
• Subjects: CALCULATING; COMPUTING; COUNTING; IMAGE DATA PROCESSING OR GENERATION, IN GENERAL; PHYSICS

Techniques for determining depth for a visual content item using machine-learning classifiers include obtaining a visual content item of a reference light pattern projected onto an object, and determining shifts in locations of pixels relative to other pixels representing the reference light pattern. Disparity, and thus depth, for pixels may be determined by executing one or more classifiers trained to identify disparity for pixels based on the shifts in locations of the pixels relative to other pixels of a visual content item depicting in the reference light pattern. Disparity for pixels may be determined using a visual content item of a reference light pattern projected onto an object without having to match pixels between two visual content items, such as a reference light pattern and a captured visual content item.