The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Aug. 20, 2019

Filed:

Apr. 27, 2016
Applicants:

Jeff Hershey, State College, PA (US);

Rajeev Sharma, State College, PA (US);

Richard Hirata, State College, PA (US);

Krishna Botla, State College, PA (US);

Inventors:

Jeff Hershey, State College, PA (US);

Rajeev Sharma, State College, PA (US);

Richard Hirata, State College, PA (US);

Krishna Botla, State College, PA (US);

Assignee:

VideoMining Corporation, State College, PA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06Q 10/00 (2012.01); G06Q 30/02 (2012.01); H04N 5/247 (2006.01); G06K 9/00 (2006.01);
U.S. Cl.
CPC ...
G06Q 30/0201 (2013.01); G06K 9/00771 (2013.01); H04N 5/247 (2013.01);
Abstract

A method and system for analyzing product strength or brand strength by determining shopper decision behavior during a shopping trip. Specifically, shopper behavior can be analyzed to determine whether a shopper's decision to purchase an item occurred at-shelf or pre-shelf. Aggregating decision data across many shoppers over time can then be used to generate analytics regarding the strength of a product or brand. The analysis can then be used to make recommendations to manufacturers or retailers about how to strengthen the product or brand. A deployment of cameras and mobile signal sensors can be utilized to recognize shoppers and track their behavior. Demographics information can also be estimated about the tracked shoppers. The visual and mobile signal trajectories can be fused to form a single shopper trajectory, then associated with Point of Sale (PoS) data. This results in a dataset describing the shopping trip for each tracked shopper.


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