# US 2014/0153788 A1 · System and methods for feature selection and matching > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2014/0153788 A1 - Document ID: US20140153788A1 - Status: Published application - Kind: A1 - Application number: 13/692,436 - Filed: 2012-12-03 - Published: 2014-06-05 - Earliest claimed: 2012-12-03 - Assignees: Honeywell International Inc. - Applicants: Honeywell International Inc. - Inventors: Yunqian Ma; Benjamin Mohr; Christopher Jon Visker - Web page: https://patentgrep.com/patent/US20140153788A1 ## CPC - G06V 30/422: Technical drawings; Geographical maps - G01C 21/005: {with correlation of navigation data from several sources, e.g. map or contour matching (G01C21/30 takes precedence)} - G01C 21/3602: {Input other than that of destination using image analysis, e.g. detection of road signs, lanes, buildings, real preceding vehicles using a camera} - G06T 7/73: using feature-based methods - G06V 20/56: exterior to a vehicle by using sensors mounted on the vehicle - G06V 20/653: {by matching three-dimensional models, e.g. conformal mapping of Riemann surfaces} - G06T 2207/10028: Range image; Depth image; 3D point clouds - G06T 2207/30252: Vehicle exterior; Vicinity of vehicle - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING - G01C: MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY (measuring liquid level G01F; radio navigation, determining distance or velocity by use of propagation effects, e.g. Doppler effects, propagation time, of radio waves, analogous arrangements using other waves G01S) - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL ## Abstract Systems and methods for feature selection and matching are provided. In certain embodiments, a method for matching features comprises extracting a first plurality of features from current image data acquired from at least one sensor and extracting a second plurality of features from a prior map, wherein the prior map represents an environment containing the navigation system independently of data currently acquired by the at least one sensor. The method also comprises identifying at least one first feature in the first plurality of features and at least one second feature in the second plurality of features that have associated two-dimensional representations; and identifying at least one corresponding pair of features by comparing a three-dimensional representations of the at least one first feature to a three-dimensional representation of the at least one second feature. ## Claims ### Claim 1 A navigation system, the system comprising: at least one sensor configured to acquire a three-dimensional representation of the environment containing the navigation system; a memory unit configured to store executable instructions and a prior map of the environment, wherein the prior map represents the environment containing the navigation system independently of data currently acquired by the at least one sensor; and a processing unit configured to execute the executable instructions, wherein the executable instructions direct the processing unit to: extract a first plurality of features from current image data; extract a second plurality of features from the prior map; compare two-dimensional representations of the first plurality of features to two-dimensional representations of the second plurality of features to find at least one first feature in the first plurality of features that associate with at least one second feature in the second plurality of features; and compare a three-dimensional representations of the at least one first feature to a three-dimensional representation of the at least one second feature to identify at least one corresponding pair of features. ### Claim 2 (depends on 1) The navigation system of claim 1, wherein the processing unit is further configured to: divide the current image data into a plurality of image data segments; divide the prior map into a plurality of map segments; select an image data segment from the plurality of image data segments and a map segment from the plurality of map segments; and extract the first plurality of features from the image data segment and the second plurality of features from the map segment. ### Claim 3 (depends on 2) The navigation system of claim 2, wherein the processing unit selects the image data segment and the map segment based on an estimated position of the navigation system within the environment. ### Claim 4 (depends on 1) The navigation system of claim 1, wherein the at least one first feature is a first set of features and the at least one second feature is a second set of features, wherein an image feature in the first set of features is associated with at least one map feature in the second set of features and the associated features are ordered according to a likelihood of corresponding to one another. ### Claim 5 (depends on 1) The navigation system of claim 1, wherein the prior map is a database storing terrain information of the environment. ### Claim 6 (depends on 1) The navigation system of claim 1, wherein the three-dimensional representation is a three-dimensional histogram. ### Claim 7 (depends on 6) The navigation system of claim 6, wherein the three-dimensional histogram is centered on data associated with the location of a feature. ### Claim 8 (depends on 6) The navigation system of claim 6, wherein the three-dimensional histogram illustrates the position of a feature and neighboring environment along the surface of the terrain and the difference between the elevation of a surface of the feature and the surface of the neighboring environment. ### Claim 9 (depends on 1) The navigation system of claim 1, wherein features are extracted using at least one of: a scale-invariant feature transform extraction method; a speeded up robust features extraction method; and a Kanade Lucas Tomasi feature extraction method. ### Claim 10 (depends on 1) The navigation system of claim 1, wherein two-dimensional representations of features are associated with one another according to feature identifiers calculated when the features were extracted. ### Claim 11 (depends on 1) The navigation system of claim 1, wherein the processing unit is further configured to identify a navigation solution for the navigation system based in part on the location of the features in the matched pair of features in relation to the navigation system. ### Claim 12 A method for matching features, the method comprising: extracting a first plurality of features from current image data acquired from at least one sensor; extracting a second plurality of features from a prior map, wherein the prior map represents an environment containing the navigation system independently of data currently acquired by the at least one sensor; identifying at least one first feature in the first plurality of features and at least one second feature in the second plurality of features that have associated two-dimensional representations; and identifying at least one corresponding pair of features by comparing a three-dimensional representations of the at least one first feature to a three-dimensional representation of the at least one second feature. ### Claim 13 (depends on 12) The method of claim 12, further comprising: determining the location of the at least one corresponding pair of features in relation to the location of the at least one image sensor; and determining a navigation solution for a vehicle having the at least one sensor mounted thereon based in part on the location of the features in the corresponding pair of features in relation to the at least one image sensor; and providing at least one of the navigation solution to a user through a human machine interface and commands based on the navigation solution to control the motion of a vehicle. ### Claim 14 (depends on 12) The method of claim 12, further comprising: dividing the current image data into a plurality of image data segments; dividing the prior map into a plurality of map segments; selecting an image data segment from the plurality of image data segments and a map segment from the plurality of map segments; and extracting the first plurality of features from the image data segment and the second plurality of features from the map segment. ### Claim 15 (depends on 12) The method of claim 12, wherein the at least one first feature is a first set of features and the at least one second feature is a second set of features, wherein an image features in the first set of features is associated with at least one map feature in the second set of features and the associated features are ordered according to a likelihood of corresponding to one another. ### Claim 16 (depends on 12) The method of claim 12, wherein the prior map is a database storing terrain information of the environment. ### Claim 17 (depends on 12) The method of claim 12, wherein the three-dimensional representation is a three-dimensional histogram. ### Claim 18 (depends on 12) The method of claim 12, wherein the three-dimensional histogram is centered on data associated with the location of a feature. ### Claim 19 A program product for identifying corresponding features, the program product comprising a plurality of instructions tangibly stored on a non-transitory storage medium, the instructions operable, when executed, to cause a processing unit to: extract a first plurality of features from current image data acquired from at least one sensor configured to acquire a three-dimensional representation of an environment containing the at least one sensor; extract a second plurality of features from a prior map of the environment, wherein the prior map represents the environment independently of data currently acquired by the at least one sensor; identify at least one first feature in the first plurality of features and at least one second feature in the second plurality of features that have associated two-dimensional representations; and identify at least one corresponding pair of features by comparing a three-dimensional histogram of the at least one first feature to a three-dimensional histogram of the at least one second feature. ### Claim 20 (depends on 19) The program product of claim 19, wherein the instruction are further operable to cause the processing unit to calculate a navigation solution for a vehicle having the at least one sensor mounted thereon, wherein the calculation is based in part on the location of the features in the at least one corresponding pair of features in relation to the vehicle.