Invention Grant
- Patent Title: Method and system for semantic change detection using deep neural network feature correlation
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Application No.: US17006558Application Date: 2020-08-28
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Publication No.: US11200657B2Publication Date: 2021-12-14
- Inventor: Jayavardhana Rama Gubbi Lakshminarasimha , Akshaya Ramaswamy , Balamuralidhar Purushothaman , Ram Prabhakar Kathirvel , Venkatesh Babu Radhakrishnan
- Applicant: TATA CONSULTANCY SERVICES LIMITED
- Applicant Address: IN Mumbai
- Assignee: TATA CONSULTANCY SERVICES LIMITED
- Current Assignee: TATA CONSULTANCY SERVICES LIMITED
- Current Assignee Address: IN Mumbai
- Agency: Finnegan, Henderson, Farabow, Garrett & Dunner, LLP
- Priority: IN201921035115 20190830
- Main IPC: G06K9/00
- IPC: G06K9/00 ; G06T7/00

Abstract:
State of the art image processing techniques such as background subtraction, and Convolutional Neural Network based approaches, when used for change detection, fail to support certain datasets. The disclosure herein generally relates to semantic change detection, and, more particularly, to a method and system for semantic change detection using a deep neural network feature correlation approach. An adaptive correlation layer is used by the system, which determines extent of computation required at pixel level, based on amount of information at pixels, and uses this information in further computation done for the semantic change detection. Information on the determined extent of computation required is then used to extract semantic features, which is then used to compute one or more correlation maps between the at least one feature map of a test image and corresponding reference image. Further the semantic changes are determined from the one or more correlation maps.
Public/Granted literature
- US20210065354A1 METHOD AND SYSTEM FOR SEMANTIC CHANGE DETECTION USING DEEP NEURAL NETWORK FEATURE CORRELATION Public/Granted day:2021-03-04
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