Abstract: A method for simultaneous localization and mapping (SLAM) employs dual event-based cameras. Event streams from the cameras are processed by an image processing system to stereoscopically detect surface points in an environment, dynamically compute pose of a camera as it moves, and concurrently update a map of the environment. A gradient descent based optimization may be utilized to update the pose for each event or for each small batch of events.

Abstract: A method for simultaneous localization and mapping (SLAM) employs dual event-based cameras. Event streams from the cameras are processed by an image processing system to stereoscopically detect surface points in an environment, dynamically compute pose of a camera as it moves, and concurrently update a map of the environment. A gradient descent based optimization may be utilized to update the pose for each event or for each small batch of events.

Abstract: A method for simultaneous localization and mapping (SLAM) employs dual event-based cameras. Event streams from the cameras are processed by an image processing system to stereoscopically detect surface points in an environment, dynamically compute pose of a camera as it moves, and concurrently update a map of the environment. A gradient descent based optimization may be utilized to update the pose for each event or for each small batch of events.

Abstract: A method for simultaneous localization and mapping (SLAM) employs dual event-based cameras. Event streams from the cameras are processed by an image processing system to stereoscopically detect surface points in an environment, dynamically compute pose of a camera as it moves, and concurrently update a map of the environment. A gradient descent based optimization may be utilized to update the pose for each event or for each small batch of events.

Abstract: Methods, apparatuses, and systems are described for positional tracking (PT) in Augmented Reality (AR) applications. The method may include creating different images for AR preview and PT applications. In some cases, the PT information utilizes key point information. The AR preview and the PT images may be generated simultaneously using time division, space division, split timing, or any combination thereof. This may result in PT with significantly less motion blur. Accordingly, the PT will be more robust, and there will be more good frames available for key components of a PT algorithm (i.e., using visual PT to calibrate the biases of an inertial measurement unit). Thus, the methods and apparatus of the present disclosure may enable more effective management of the trade-off between motion-blur, noise and resolution for PT.

Abstract: Methods, apparatuses, and systems are described for positional tracking (PT) in Augmented Reality (AR) applications. The method may include creating different images for AR preview and PT applications. In some cases, the PT information utilizes key point information. The AR preview and the PT images may be generated simultaneously using time division, space division, split timing, or any combination thereof. This may result in PT with significantly less motion blur. Accordingly, the PT will be more robust, and there will be more good frames available for key components of a PT algorithm (i.e., using visual PT to calibrate the biases of an inertial measurement unit). Thus, the methods and apparatus of the present disclosure may enable more effective management of the trade-off between motion-blur, noise and resolution for PT.

Abstract: Methods, apparatuses, and systems are described for positional tracking (PT) in Augmented Reality (AR) applications. The method may include creating different images for AR preview and PT applications. In some cases, the PT information utilizes key point information. The AR preview and the PT images may be generated simultaneously using time division, space division, split timing, or any combination thereof. This may result in PT with significantly less motion blur. Accordingly, the PT will be more robust, and there will be more good frames available for key components of a PT algorithm (i.e., using visual PT to calibrate the biases of an inertial measurement unit). Thus, the methods and apparatus of the present disclosure may enable more effective management of the trade-off between motion-blur, noise and resolution for PT.

Abstract: Methods, apparatuses, and systems are described for positional tracking (PT) in Augmented Reality (AR) applications. The method may include creating different images for AR preview and PT applications. In some cases, the PT information utilizes key point information. The AR preview and the PT images may be generated simultaneously using time division, space division, split timing, or any combination thereof. This may result in PT with significantly less motion blur. Accordingly, the PT will be more robust, and there will be more good frames available for key components of a PT algorithm (i.e., using visual PT to calibrate the biases of an inertial measurement unit). Thus, the methods and apparatus of the present disclosure may enable more effective management of the trade-off between motion-blur, noise and resolution for PT.

Abstract: A method for simultaneous localization and mapping (SLAM) employs dual event-based cameras. Event streams from the cameras are processed by an image processing system to stereoscopically detect surface points in an environment, dynamically compute pose of a camera as it moves, and concurrently update a map of the environment. A gradient descent based optimization may be utilized to update the pose for each event or for each small batch of events.