Snap Inc.

Olha Borys

Jakob Zillner

Matthias Kalkgruber

Daniel Wolf

Ilteris Kaan Canberk

Georg Halmetschlager-Funek

Daniel Wagner

Lien Le Hong Tran

Tobias Maier

A system is disclosed, including a processor and a memory. The memory stores instructions that, when executed by the processor, configure the system to perform operations. Surface plane information is obtained, defining a surface plane passing through a surface location and oriented according to a surface normal. An edge is detected in an image. Virtual content is presented, having a virtual position based on an orientation of the edge and the surface plane information.

Alignment of augmented reality components with the physical world

Disclosed are systems, methods, and non-transitory computer-readable media for continuous surface and depth estimation. A continuous surface and depth estimation system determines the depth and surface normal of physical objects by using stereo vision limited within a predetermined window.

Continuous surface and depth estimation

Visual-inertial tracking of an eyewear device using sensors. The eyewear device monitors the sensors of a visual inertial odometry system (VIOS) that provide input for determining a position of the device within its environment. The eyewear device determines the status of the VIOS based information from the sensors and adjusts the plurality of sensors (e.g., by turning on/off sensors, changing the sampling rate, of a combination thereof) based on the determined status. The eyewear device then determines the position of the eyewear device within the environment using the adjusted plurality of sensors.

Dynamic sensor selection for visual inertial odometry systems

A method for mitigating motion blur in a visual tracking system is described. In one aspect, a method for selective motion blur mitigation in a visual tracking system includes accessing a first image generated by an optical sensor of the visual tracking system, identifying camera operating parameters of the optical sensor during the optical sensor generating the first image, determining a motion of the optical sensor during the optical sensor generating the first image, determining a motion blur level of the first image based on the camera operating parameters of the optical sensor and the motion of the optical sensor, and determining whether to downscale the first image using a pyramid computation algorithm based on the motion blur level.

Selective image pyramid computation for motion blur mitigation in visual-inertial tracking

Disclosed are systems, methods, and non-transitory computer-readable media for misaligned vantage point mitigation for computer stereo vision. A misaligned vantage point mitigation system determines whether vantage points of the optical sensors are misaligned from an expected vantage point and, if so, determines an adjustment variable to mitigate the misalignment based on the location of matching features identified in images captured by both optical sensors.

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Vienna, Austria

Olha Borys