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Guruprasad P Shivaram

from Wellesley, MA
Age ~54
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Also known as:
Guruprasad Shivar, Guruprasad Shivram, Guruprasad Shivaran, Shivaram Guruprasad, Guruprasad M
Phone and address:
48 Halsey Ave, Wellesley, MA 02482
Related to:
Vishal Rao
Connected to:
Anil Shivaram, 50Charishma G Shivaratri, 46Mimi Shivar, 58Bhargav G Shivarthy, 42Ranjitha Shivarudraiah, 40Deepak Shivashankar, 47Preethi Shivashankar, 33Tumkur S Shivashankara, 84Suresh R Shivdasani, 66Urvashi Shivdasani, 50

Guruprasad Shivaram Phones & Addresses

  • 48 Halsey Ave, Wellesley, MA 02482
  • 90 Sherman St, Chestnut Hill, MA 02467 (617) 327-0639
  • 50 Dinsmore Ave, Framingham, MA 01702 (508) 879-0486
  • 264 Grove St, Auburndale, MA 02466 (617) 332-1016
  • 3146 Dorchester Cir, Madison, WI 53719 (608) 278-8133
  • 226 Randolph Dr, Madison, WI 53717 (608) 827-0880
  • 7102 Flagship Dr, Madison, WI 53719 (608) 278-8133
  • Lafayette, LA

Work

Company: Cognex corporation 2005 to 2017 Position: Principal engineer at cognex corporation

Education

Degree: Doctorates, Doctor of Philosophy School / High School: University of Louisiana at Lafayette 1994 to 1998 Specialities: Computer Engineering

Skills

Image Processing • Algorithms • Computer Vision • Object Oriented Design • Software Engineering • Machine Vision • Signal Processing • C++ • C • Digital Signal Processors • Software Development • Pattern Recognition • Dsp • Qt

Industries

Computer Software

Resumes

Resumes

Guruprasad Shivaram Photo 1

Consulting Software Engineer

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Location:
318 Seaboard Ln, Franklin, TN 37067
Industry:
Computer Software
Work:
Cognex Corporation 2005 - 2017
Principal Engineer at Cognex Corporation
Cognex Corporation 2005 - 2017
Consulting Software Engineer
Automated Vision 1998 - 2005
Scientist
Education:
University of Louisiana at Lafayette 1994 - 1998
Doctorates, Doctor of Philosophy, Computer Engineering Indian Institute of Technology, Madras 1991 - 1993
R. V. College of Engineering, Bangalore 1987 - 1991
Bachelor of Engineering, Bachelors
Skills:
Image Processing
Algorithms
Computer Vision
Object Oriented Design
Software Engineering
Machine Vision
Signal Processing
C++
C
Digital Signal Processors
Software Development
Pattern Recognition
Dsp
Qt

Publications

Us Patents

System And Method For Three-Dimensional Alignment Of Objects Using Machine Vision

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US Patent:
20100166294, Jul 1, 2010
Filed:
Dec 29, 2008
Appl. No.:
12/345130
Inventors:
Cyril C. Marrion - Acton MA, US
Nigel J. Foster - Natick MA, US
Lifeng Liu - Arlington MA, US
David Y. Li - West Roxbury MA, US
Guruprasad Shivaram - Chestnut Hill MA, US
Aaron S. Wallack - Natick MA, US
Xiangyun Ye - Framingham MA, US
Assignee:
COGNEX CORPORATION - Natick MA
International Classification:
G06K 9/00
US Classification:
382154
Abstract:
This invention provides a system and method for determining the three-dimensional alignment of a modeledobject or scene. After calibration, a 3D (stereo) sensor system views the object to derive a runtime 3D representation of the scene containing the object. Rectified images from each stereo head are preprocessed to enhance their edge features. A stereo matching process is then performed on at least two (a pair) of the rectified preprocessed images at a time by locating a predetermined feature on a first image and then locating the same feature in the other image. 3D points are computed for each pair of cameras to derive a 3D point cloud. The 3D point cloud is generated by transforming the 3D points of each camera pair into the world 3D space from the world calibration. The amount of 3D data from the point cloud is reduced by extracting higher-level geometric shapes (HLGS), such as line segments. Found HLGS from runtime are corresponded to HLGS on the model to produce candidate 3D poses. A coarse scoring process prunes the number of poses. The remaining candidate poses are then subjected to a further more-refined scoring process. These surviving candidate poses are then verified by, for example, fitting found 3D or 2D points of the candidate poses to a larger set of corresponding three-dimensional or two-dimensional model points, whereby the closest match is the best refined three-dimensional pose.

System And Method For Runtime Determination Of Camera Miscalibration

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US Patent:
20110157373, Jun 30, 2011
Filed:
Dec 24, 2009
Appl. No.:
12/647192
Inventors:
Xiangyun Ye - Framingham MA, US
David Y. Li - West Roxbury MA, US
Guruprasad Shivaram - Chestnut Hill MA, US
David J. Michael - Wayland MA, US
Assignee:
COGNEX CORPORATION - Natick MA
International Classification:
H04N 17/00
US Classification:
348187, 348E07085
Abstract:
This invention provides a system and method for runtime determination (self-diagnosis) of camera miscalibration (accuracy), typically related to camera extrinsics, based on historical statistics of runtime alignment scores for objects acquired in the scene, which are defined based on matching of observed and expected image data of trained object models. This arrangement avoids a need to cease runtime operation of the vision system and/or stop the production line that is served by the vision system to diagnose if the system's camera(s) remain calibrated. Under the assumption that objects or features inspected by the vision system over time are substantially the same, the vision system accumulates statistics of part alignment results and stores intermediate results to be used as indicator of current system accuracy. For multi-camera vision systems, cross validation is illustratively employed to identify individual problematic cameras. The system and method allows for faster, less-expensive and more-straightforward diagnosis of vision system failures related to deteriorating camera calibration.

System And Method For Calibration Of Machine Vision Cameras Along At Least Three Discrete Planes

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US Patent:
20210012532, Jan 14, 2021
Filed:
May 22, 2020
Appl. No.:
16/882273
Inventors:
- Natick MA, US
Guruprasad Shivaram - Wellesley MA, US
International Classification:
G06T 7/80
H04N 5/232
H04N 5/225
H04N 17/00
Abstract:
This invention provides a system and method for generating camera calibrations for a vision system camera along three discrete planes in a 3D volume space that uses at least two (e.g. parallel) object planes at different known heights. For any third (e.g. parallel) plane of a specified height, the system and method then automatically generates calibration data for the camera by interpolating/extrapolating from the first two calibrations. This alleviates the need to set the calibration object at more than two heights, speeding the calibration process and simplifying the user's calibration setup, and also allowing interpolation/extrapolation to heights that are space-constrained, and not readily accessible by a calibration object. The calibration plate can be calibrated at each height using a full 2D hand-eye calibration, or using a hand-eye calibration at the first height and then at a second height with translation to a known position along the height (e.g. Z) direction.

System And Method For Calibration Of Machine Vision Cameras Along At Least Three Discrete Planes

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US Patent:
20140240520, Aug 28, 2014
Filed:
Feb 25, 2013
Appl. No.:
13/776617
Inventors:
Cognex Corporation - , US
Guruprasad Shivaram - Chestnut Hill MA, US
Assignee:
COGNEX CORPORATION - Natick MA
International Classification:
H04N 17/00
US Classification:
348187
Abstract:
This invention provides a system and method for generating camera calibrations for a vision system camera along three discrete planes in a 3D volume space that uses at least two (e.g. parallel) object planes at different known heights. For any third (e.g. parallel) plane of a specified height, the system and method then automatically generates calibration data for the camera by interpolating/extrapolating from the first two calibrations. This alleviates the need to set the calibration object at more than two heights, speeding the calibration process and simplifying the user's calibration setup, and also allowing interpolation/extrapolation to heights that are space-constrained, and not readily accessible by a calibration object. The calibration plate can be calibrated at each height using a full 2D hand-eye calibration, or using a hand-eye calibration at the first height and then at a second height with translation to a known position along the height (e.g. Z) direction.
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Guruprasad P Shivaram from Wellesley, MA, age ~54 Get Report