US 12,217,479 B2
Using a probabilistic model for detecting an object in visual data
George Saklatvala, Cambridge (GB)
Assigned to Open Text Corporation, Waterloo (CA)
Filed by Open Text Corporation, Waterloo (CA)
Filed on May 10, 2022, as Appl. No. 17/741,211.
Application 17/741,211 is a continuation of application No. 16/891,923, filed on Jun. 3, 2020, granted, now 11,341,738.
Application 16/891,923 is a continuation of application No. 16/532,702, filed on Aug. 6, 2019, granted, now 10,699,158, issued on Jun. 30, 2020.
Application 16/532,702 is a continuation of application No. 15/864,839, filed on Jan. 8, 2018, granted, now 10,417,522, issued on Sep. 17, 2019.
Application 15/864,839 is a continuation of application No. 15/420,515, filed on Jan. 31, 2017, granted, now 9,892,339, issued on Feb. 13, 2018.
Application 15/420,515 is a continuation of application No. 14/434,056, granted, now 9,594,942, issued on Mar. 14, 2017, previously published as PCT/EP2012/070159, filed on Oct. 11, 2012.
Prior Publication US 2022/0277543 A1, Sep. 1, 2022
Int. Cl. G06V 10/75 (2022.01); G06F 18/22 (2023.01); G06V 20/64 (2022.01); H04L 67/10 (2022.01)
CPC G06V 10/757 (2022.01) [G06F 18/22 (2023.01); G06V 10/75 (2022.01); G06V 20/653 (2022.01); H04L 67/10 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method, comprising:
building, by an object recognition system, a probabilistic model for each respective object of a plurality of objects representing different object types, the building utilizing statistics for matches between simulated views of the respective object and other objects and statistics for non-matches between reference images that do not contain the respective object and the other objects, wherein the building produces probabilistic models for the different object types;
receiving, by the object recognition system, input visual data; and
determining, by the object recognition system utilizing the probabilistic models for the different object types, whether objects of the different object types are present in the input visual data, wherein the determining comprises mapping, utilizing the probabilistic models, a probability threshold to different number thresholds for the different object types, and wherein each number threshold of the different number thresholds indicates a number of matching features above which an object of a corresponding object type is considered to be present in the input visual data.