IP Library Granted Patent US 9,418,458
Granted Patent B2
US 9,418,458 · App. 14/987,479 · Granted Aug 16, 2016

Graph image representation from convolutional neural networks

Inventors: Michael Chertok (Raanana, IL); Alexander Lorbert (Givat Shmuel, IL)
Assignee: SUPERFISH LTD.
G06T11/206G06K9/66G06T7/0085
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Quick Facts
Patent No.
US 9,418,458
App. No.
14/987,479
Granted
Aug 16, 2016
Kind
B2
Abstract

A method for producing a graph representation of an input image, the method including the procedures of applying convolutional layers of a trained convolutional neural network on the input image, defining a receptive field of a last convolutional layer of the trained convolutional neural network as a vertex of the graph representation, defining a vector of a three dimensional output matrix of the last convolutional layer that is mapped to the receptive field as a descriptor for the vertex and determining an edge between a pair of vertices of the graph representation by applying an operator on a pair of descriptors respective of the pair of vertices.

Claims (9)

1. A method for producing a graph representation of an input image, the method comprising the procedures of:

applying convolutional layers of a trained convolutional neural network on said input image;

defining a receptive field of a last convolutional layer of said trained convolutional neural network as a vertex of said graph representation;

defining a vector of a three dimensional output matrix of said last convolutional layer that is mapped to said receptive field as a descriptor for said vertex; and

determining an edge between a pair of vertices of said graph representation by applying an operator on a pair of descriptors respective of said pair of vertices.

2. The method according to claim 1 , further comprising a procedure of employing said graph representation of said input image for performing a visual task.

3. The method according to claim 1 , wherein said procedure of determining an edge further comprises a sub-procedure of scaling said edge according to a distance between said vertices of said pair of vertices.

4. The method according to claim 1 , wherein only a portion of said convolutional layers are applied on said input image.

5. The method according to claim 1 , further comprising a procedure of applying at least one fully connected layer of said trained convolutional neural network on said input image after said procedure of applying convolutional layers, and further comprising a procedure of backtracking an output of said at least one fully connected layer to said last convolutional layer.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 4, 2016
From: CHERTOK, MICHAEL; LORBERT, ALEXANDER
To: SUPERFISH LTD.
Reel/Frame 037403/0657 →
Priority Claims (1)
IL 236596 · Jan 5, 2015 · national
Continuity (1)
Related Publication 20160196672A1 · Jul 7, 2016