Location recognition using informative feature vocabulary trees

A system for location recognition using a query image depicting a location it is desired to identify and a database of features associated with images of known locations, comprising:

• a general purpose computing device;
• a computer program comprising program modules executable by the computing device, wherein the computing device is directed by the program modules of the computer program to,
• generate query image features representative of the query image using the same technique as used to generate the database features resident in the database from the known location images;
• for each feature associated with the query image, input the query image feature into an informative feature vocabulary tree and identify two or more visual words output by the vocabulary tree for that query image feature, wherein the informative feature vocabulary tree was generated using just those database features that have been deemed informative of the known locations and was used to assign visual words to each known location image that are output from the tree whenever a database feature associated with that image is input into the tree;
• identify the known location image having the most visual words in common with the query image;
• and
• designate the location associated with the identified known location image as the location depicted in the query image.

A system for searching a metric tree, comprising:

• a general purpose computing device;
• a computer program comprising program modules executable by the computing device, wherein the computing device is directed by the program modules of the computer program to,
• (a) establish a number of search paths N, wherein N is greater than 1,
• (b) input a query into the root node of the metric tree,
• (c) computing the distance between the query and each child node of the root node,
• (d) designating N child nodes having the closest computed distances to the query as candidate nodes for the next level of the metric tree,
• (e) designating the next level of the metric tree to be the current level,
• (f) computing the distance between the query and each child node of just the candidate nodes of the current level,
• (g) repeating sub-modules (d) through (f) until the next level of the metric tree in relation to the current level is the last level of the tree, and
• (h) designating the N child nodes having the closest computed distances to the query as the output of the metric tree.