Locating persons of interest based on license plate recognition information

• US 9,542,620 B1
• Filed: 06/06/2016
• Issued: 01/10/2017
• Est. Priority Date: 07/26/2011
• Status: Active Grant

• Current Assignee: VaaS International Holdings, Inc. (Motorola Solutions, Inc.)
• Original Assignee: VaaS, Inc.
• Inventors: Smith, Shawn B.
• Primary Examiner(s): AZARIAN, SEYED H
• Application Number:
  US15/174,600
• Time in Patent Office: 218 Days
• Field of Search: 382/100, 382103-107, 382/155, 382/162, 382/168, 382/173, 382/181, 382/193, 382/209, 382/219, 382/224, 382/232, 382/254, 382/274, 382/276, 382287-291, 382/305, 382/312, 382/321, 382/116, 340/933, 340/937, 340/932.2, 235/384, 705/13
• US Class Current: 1/1
• CPC Class Codes: G06F 16/29 Geographical information databases
• CPC Class Codes: G06F 18/2113 by ranking or filtering the set of features, e.g. using a measure of variance or of feature cross-correlation
• CPC Class Codes: G06F 18/22 Matching criteria, e.g. proximity measures
• CPC Class Codes: G06F 18/23 Clustering techniques
• CPC Class Codes: G06F 18/232 Non-hierarchical techniques
• CPC Class Codes: G06T 2207/30232 Surveillance
• CPC Class Codes: G06T 2207/30252 Vehicle exterior; Vicinity of vehicle
• CPC Class Codes: G06T 7/70 Determining position or orientation of objects or cameras camera calibration G06T7/80
• CPC Class Codes: G06V 10/768 using context analysis, e.g. recognition aided by known co-occurring patterns
• CPC Class Codes: G06V 20/625 License plates
• CPC Class Codes: G08G 1/0175 by photographing vehicles, e.g. when violating traffic rules

Abstract

Possible locations of a person of interest are ranked based on LPR instances captured around physical locations and license plate numbers associated with the person of interest. An LPR instance includes an indication of a vehicle license plate number, a physical location, and a time when the LPR instance was captured by a LPR system. A possible location of the person of interest may be a location of an LPR instance that matches the license plate number or an address location associated with the person of interest. The ranking may be based on the number of LPR visits to each location, the number of license plate number matches at each location, or an attribute of a cluster of LPR instances. In some examples, an electronic message is rapidly communicated to an entity if a target license plate number is found at a highly ranked location.

Claims

1. A method comprising:

receiving an indication of a license plate number of a vehicle associated with a person of interest onto a computing system including a non-transitory computer readable medium storing an amount of program code that when executed by the computing system is for;

determining a plurality of License Plate Recognition (LPR) instances recognized within a search zone around any of a plurality of possible locations of the person of interest, wherein a possible location of the person of interest includes any of a location of an LPR instance that matches the license plate number and an address location associated with the person of interest;

determining a plurality of clusters of recognized LPR instances based on a visiting time period that an LPR unit collected LPR instances within the search zone, wherein the determining of the plurality of clusters involves determining a time difference between successive LPR instances and assigning the successive LPR instances to the same cluster if the time difference is less than a predetermined threshold value;

determining at least one attribute of each of the clusters;

ranking the plurality of possible locations of the person of interest based at least in part on the at least one attribute of each of the clusters of LPR instances; and

communicating a list of address locations and time periods where the person of interest may be reached based on the ranking of the plurality of possible locations of the person of interest.

2. The method of claim 1, wherein an LPR instance of the plurality of LPR instances includes an indication of a vehicle license plate number, an indication of a physical location, and an indication of a time when the LPR instance was captured by a LPR system.

3. The method of claim 1, wherein an LPR visit is a period of time when an LPR unit approached a particular location, collected LPR information, and subsequently left the particular location.

4. The method of claim 1, further comprising:

determining a time of day associated with each cluster of recognized LPR instances associated with a possible location of the person of interest; and

identifying a property type of the possible location based at least in part on the time of day associated with each cluster of recognized LPR instances associated with the possible location and the number of LPR instances scanned in each cluster.

5. The method of claim 1, wherein the determining of the at least one attribute of each of the clusters involves determining a number of LPR instances that match the license plate number associated with a person of interest within each cluster of recognized LPR instances, and wherein the ranking of the clusters is based at least in part on the determined number of LPR instances that match the license plate number associated with the person of interest within each cluster.

6. The method of claim 1, wherein the determining of the at least one attribute of each of the clusters involves determining a number of the LPR instances scanned during each of a plurality of time of day periods for each of the clusters, and wherein the ranking of the possible locations is based at least in part on the number of LPR instances scanned in each of the time of day periods.

7. The method of claim 1, wherein the determining of the at least one attribute of each of the clusters involves determining a time duration associated with each cluster, and wherein the time duration is determined based on a time difference between a time stamp associated with the earliest LPR instance of a cluster and the time stamp associated with the latest LPR instance of the cluster.

8. A method comprising:

receiving a plurality of LPR instances that include a plurality of license plate numbers within a search zone around a location onto a computing system including a non-transitory computer readable medium storing an amount of program code that when executed by the computing system is for;

determining a plurality of clusters of recognized LPR instances based on a visiting time period that an LPR unit collected LPR instances within the search zone, wherein the determining of the plurality of clusters involves determining a time difference between successive LPR instances and assigning the successive LPR instances to the same cluster if the time difference is less than a predetermined threshold value;

determining at least one attribute of each of the clusters;

ranking the plurality of possible locations of the person of interest based at least in part on the at least one attribute of each of the clusters of LPR instances; and

communicating a list of address locations and time periods where the person of interest may be reached based on the ranking of the plurality of possible locations of the person of interest.

9. An apparatus comprising:

a processor; and

a non-transitory computer readable medium storing an amount of program code that, when executed, causes the apparatus to;

receive an indication of a license plate number of a vehicle associated with a person of interest;

determine a plurality of License Plate Recognition (LPR) instances recognized within a search zone around any of a plurality of possible locations of the person of interest, wherein a possible location of the person of interest includes any of a location of an LPR instance that matches the license plate number and an address location associated with the person of interest;

determine a plurality of clusters of recognized LPR instances based on a visiting time period that an LPR unit collected LPR instances within the search zone, wherein the determining of the plurality of clusters involves determining a time difference between successive LPR instances and assigning the successive LPR instances to the same cluster if the time difference is less than a predetermined threshold value;

determine at least one attribute of each of the clusters;

rank the plurality of possible locations of the person of interest based at least in part on the at least one attribute of each of the clusters of LPR instances; and

communicate a list of address locations and time periods where the person of interest may be reached based on the ranking of the plurality of possible locations of the person of interest.

10. The apparatus of claim 9, wherein an LPR instance of the plurality of LPR instances includes an indication of a vehicle license plate number, an indication of a physical location, and an indication of a time when the LPR instance was captured by a LPR system.

11. The apparatus of claim 9, wherein an LPR visit is a period of time when an LPR unit approached a particular location, collected LPR information, and subsequently left the particular location.

12. The apparatus of claim 9, the non-transitory computer readable medium also storing an amount of program code that, when executed, causes the apparatus to:

determine a time of day associated with each cluster of recognized LPR instances associated with a possible location of the person of interest; and

identify a property type of the possible location based at least in part on the time of day associated with each cluster of recognized LPR instances associated with the possible location and the number of LPR instances scanned in each cluster.

13. The apparatus of claim 9, wherein the determining of the at least one attribute of each of the clusters involves determining a number of LPR instances that match the license plate number associated with a person of interest within each cluster of recognized LPR instances, and wherein the ranking of the clusters is based at least in part on the determined number of LPR instances that match the license plate number associated with the person of interest within each cluster.

14. The apparatus of claim 9, wherein the determining of the at least one attribute of each of the clusters involves determining a number of the LPR instances scanned during each of a plurality of time of day periods for each of the clusters, and wherein the ranking of the possible locations is based at least in part on the number of LPR instances scanned in each of the time of day periods.

15. The apparatus of claim 9, wherein the determining of the at least one attribute of each of the clusters involves determining a time duration associated with each cluster, and wherein the time duration is determined based on a time difference between a time stamp associated with the earliest LPR instance of a cluster and the time stamp associated with the latest LPR instance of the cluster.