Prior informed pose and scale estimation

A computing system comprising:

• one or more logic machines;
• one or more storage machines holding instructions executable by the one or more logic machines to:
• receive camera data for a scene acquired by one or more cameras of a camera system;
• receive a rotation prior parameter characterizing a gravity direction;
• receive a scale prior parameter characterizing scale of the camera system;
• calculate a cost of a cost function for a similarity transformation that is configured to encode a scale and pose of the camera system, such calculation being performed to optimize a rotation term and a translation term of the similarity transformation, where the cost of the cost function is selectively influenced by the rotation prior parameter and the scale prior parameter;
• determine a solved similarity transformation upon calculating a cost for the cost function that is less than a threshold cost;
• and
• output an estimated scale and pose of the camera system based on the solved similarity transformation.

A scale and pose estimation method for a camera system, the method comprising:

• receiving camera data for a scene acquired by one or more cameras of the camera system;
• receiving a rotation prior parameter characterizing a gravity direction;
• receiving a scale prior parameter characterizing scale of the camera system, wherein the rotation prior parameter and the scale prior parameter are derived from measurements of one or more inertial sensors;
• calculating a cost function for a similarity transformation that is configured to encode a scale and pose of the camera system, such calculation being performed to optimize a rotation term and a translation term of the similarity transformation, where the cost of the cost function is selectively influenced by the rotation prior parameter, a rotation weight corresponding to the rotation prior parameter, the scale prior parameter and a scale weight corresponding to the scale prior parameter;
• adjusting the rotation weight and the scale weight based on the sensor noise of the one or more inertial sensors;
• determining a solved similarity transformation upon calculating a cost for the cost function that is less than a threshold cost;
• and
• outputting an estimated scale and pose of the camera system based on the solved similarity transformation.