Determining multiple camera positions from multiple videos

A system for estimating positions of multiple cameras from video recordings from each of the multiple cameras, comprising:

• a processor, and
• a computer-readable storage medium having instructions that when executed by the processor, cause the processor to:
• select a subset of frames of each video recording, wherein the processor:
• determines relative blurriness of each frame of each video recording,
• selects frames having a lowest relative blurriness,
• counts feature points in each of the lowest relative blurriness frames, and
• selects for further analysis, lowest relative blurriness frames having a highest count of feature points;
• and
• processes each selected subset of frames from each video recording to estimate the location and orientation of each camera.

A method for estimating positions of each of a plurality of cameras, comprising:

• at a processor:
• receiving video data from at least one video recording taken by each camera;
• selecting a subset of frames of each video recording, comprising:
• determining relative blurriness of each frame of each video recording,
• selecting frames having a lowest relative blurriness,
• counting feature points in each of the lowest relative blurriness frames, and
• selecting for each video recording, a subset of frames with a lowest relative blurriness and a highest count of feature points;
• mapping the feature points, comprising:
• identifying key feature points that do not vary in scale and orientation beyond a threshold amount in each of frame in the selected subset of frames;
• determining orientations of each identified key feature point;
• comparing each framed in the selected subset of frames from each video recording to each frame in a selected subset of frames from all other video recordings being analyzed;
• determining matching frames by identifying, for each frame, a neighboring frame having one or more of the same key feature points;
• selecting matched frames having similar scale and orientation;
• sorting the selected matched frames into bins;
• and
• finally selecting frames from bins having a highest count of sorted frames;
• identifying as candidate frame pairs, finally selected frames showing two-dimensional displacement of key feature points according to a threshold;
• and
• estimating focal length using the candidate frame pairs comprising:
• determining an intersection point of normals from image planes corresponding to the frames of the candidate frame pairs, and
• measuring focal length as a distance between the intersection point and a point one of the image planes.