Invention Grant
- Patent Title: Scalable distributed computation framework for data-intensive computer vision workloads
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Application No.: US15471710Application Date: 2017-03-28
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Publication No.: US10469822B2Publication Date: 2019-11-05
- Inventor: Venkatanathan Varadarajan , Arun Raghavan , Sam Idicula , Nipun Agarwal
- Applicant: Oracle International Corporation
- Applicant Address: US CA Redwood Shores
- Assignee: Oracle International Corporation
- Current Assignee: Oracle International Corporation
- Current Assignee Address: US CA Redwood Shores
- Agency: Hickman Palermo Becker Bingham LLP
- Main IPC: H04N13/128
- IPC: H04N13/128 ; G06T7/593 ; H04N13/00

Abstract:
Techniques described herein provide methods and systems for scalable distribution of computer vision workloads. In an embodiment, a method comprises receiving, at each of a first node and a second node of a distributed system of nodes, two images. The first image comprises a first set of pixels and the second image comprising a second set of pixels. The method further comprises shifting, at the first node, each pixel of the first set of pixels of the first image in a uniform direction by a first number of pixels to form a first shifted image and shifting, at the second node, each pixel of the first set of pixels of the first image in the uniform direction by a second number of pixels to form a second shifted image. The second number of pixels is different from the first number of pixels. The method further comprises overlaying each of the first shifted image and the second shifted image with the second image, such that each pixel of the first shifted image and second shifted image has a corresponding pixel in the second image. The method further comprises creating, at the first node, a first disparity map that indicates, for each pixel of the first shifted image, a level of similarity between the pixel of the first shifted image and the corresponding pixel in the second image and creating, at the second node, a second disparity map that indicates, for each pixel of the second shifted image, a level of similarity between the pixel of the second shifted image and the corresponding pixel in the second image.
Public/Granted literature
- US20180288384A1 SCALABLE DISTRIBUTED COMPUTATION FRAMEWORK FOR DATA-INTENSIVE COMPUTER VISION WORKLOADS Public/Granted day:2018-10-04
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