Estimating dimensions for an enclosed space using a multi-directional camera

A system for estimating dimensions of an enclosed space comprising:

• a monocular multi-directional camera device to capture a sequence of images from a plurality of angular positions within the enclosed space;
• a pose estimator to determine pose data from the sequence of images, the pose data indicating the location and orientation of the monocular multi-directional camera device at a plurality of positions during the instructed movement, the pose data being determined using a set of features detected within the sequence of images;
• a depth estimator to estimate depth values by evaluating a volumetric function of the sequence of images and the pose data, each depth value representing a distance from a reference position of the multi-directional camera device to a surface in the enclosed space;
• and
• a dimension estimator to:
• fit a three-dimensional volume to the depth values from the depth estimator by optimising dimensions of a two-dimensional polygonal cross-section of the three-dimensional volume, and
• output an estimate for the dimensions of the enclosed space based on the optimised dimensions of the two-dimensional polygonal cross-section.

A non-transitory computer-readable storage medium comprising computer-executable instructions which, when executed by a processor, cause a computing device to map a space, wherein the instructions cause the computing device to:

• receive a sequence of frames from a monocular multi-directional camera, the multi-directional camera being arranged to capture image data for each of the frames from a plurality of angular positions, the sequence of frames being captured at different angular positions within a plane of movement for the space;
• determine location and orientation estimates for the camera for each frame by matching detected features across the sequence of frames;
• bundle adjust the location and orientation estimates for the camera and the detected features across the sequence of frames to generate an optimised set of location and orientation estimates for the camera;
• determine a reference frame from the sequence of frames, the reference frame having an associated reference location and orientation;
• evaluate a photometric error function between pixel values for the reference frame and projected pixel values from a set of comparison images that overlap the reference frame, said projected pixel values being a function of a surface distance from the camera and the optimised set of location and orientation estimates for the camera;
• determine a first set of surface distances for different angular positions corresponding to different pixel columns of the reference frame based on the evaluated photometric error function;
• determine parameters for a planar rectangular cross-section of a three-dimensional volume enclosing the reference location by optimising an error between the first set of surface distances and a second set of surface distances determined based on the three-dimensional volume;
• and
• determine a floor plan for the space using the determined parameters for the planar rectangular cross-section.