Jason David Meltzer from Castro Valley, CA, age 38

Resumes

Principal Member Of Technical Staff

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Location:

Portland, OR

Industry:

Computer & Network Security

Work:

Oracle
Principal Member of Technical Staff
Ncc Group Jul 2016 - Nov 2018
Senior Security Consultant
Intel Corporation May 2014 - May 2016
Senior Security Researcher
Strange Research Corporation Jan 2007 - May 2014
Herder of Gibbering Horrors
Openbsd May 2009 - Nov 2013
Slacker

Education:

University of Alberta 2013
Master of Science, Masters University of Alberta 1998 - 2003
Bachelors, Bachelor of Science, Computer Engineering, Engineering

Skills:

Computer Security
Vulnerability Assessment
Security
Information Security
Firewalls
Penetration Testing
Security Research
Information Security Management
Reverse Engineering
Application Security
Network Security
Software Engineering
Tcp/Ip
Web Application Security
Cryptography
Ids
Security Architecture Design
Security Audits
Malware Analysis
Incident Response
Vulnerability Management

Jason Meltzer

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Jason Meltzer

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Location:

Portland, OR

Name / Title

Company / Classification

Phones & Addresses

Jason Meltzer
Principal

Kos
Nonclassifiable Establishments

20887 Sherman Dr, Hayward, CA 94552

Us Patents

Simultaneous Localization And Mapping Using Multiple View Feature Descriptors
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US Patent:

20050238200, Oct 27, 2005
Filed:

Dec 22, 2004
Appl. No.:

11/021672
Inventors:

Rakesh Gupta - Mountain View CA, US
Ming-Hsuan Yang - Mountain View CA, US
Jason Meltzer - Los Angeles CA, US
International Classification:

G06K009/00
G06K009/62
G06K009/46
US Classification:

382103000, 382159000, 382190000
Abstract:

Simultaneous localization and mapping (SLAM) utilizes multiple view feature descriptors to robustly determine location despite appearance changes that would stifle conventional systems. A SLAM algorithm generates a feature descriptor for a scene from different perspectives using kernel principal component analysis (KPCA). When the SLAM module subsequently receives a recognition image after a wide baseline change, it can refer to correspondences from the feature descriptor to continue map building and/or determine location. Appearance variations can result from, for example, a change in illumination, partial occlusion, a change in scale, a change in orientation, change in distance, warping, and the like. After an appearance variation, a structure-from-motion module uses feature descriptors to reorient itself and continue map building using an extended Kalman Filter. Through the use of a database of comprehensive feature descriptors, the SLAM module is also able to refine a position estimation despite appearance variations.