Rangachar Kasturi

Author:

Rangachar Kasturi

ISBN #:

0387612262

Author:

Rangachar Kasturi

ISBN #:

0818665475

Author:

Rangachar Kasturi

ISBN #:

0818691026

Author:

Rangachar Kasturi

ISBN #:

0818691034

Author:

Rangachar Kasturi

ISBN #:

0824781988

Author:

Rangachar Kasturi

ISBN #:

3540612262

US Patent:

8331632, Dec 11, 2012

Filed:

Feb 13, 2009

Appl. No.:

12/371099

Inventors:

Pranab Mohanty - Tampa FL, US
Sudeep Sarkar - Tampa FL, US
Rangachar Kasturi - Tampa FL, US
P. Jonathon Phillips - Bethesda MD, US

Assignee:

University of South Florida - Tampa FL
The United States of America, as represented by the Secretary of the Department of Commerce, the National Institute of Standards and Technology - Washington DC

International Classification:

G06K 9/00
G06K 9/62

US Classification:

382118, 382115, 382117, 382155, 382159, 382160, 726 25

Abstract:

A novel, linear modeling method to model a face recognition algorithm based on the match scores produced by the algorithm. Starting with a distance matrix representing the pair-wise match scores between face images, an iterative stress minimization algorithm is used to obtain an embedding of the distance matrix in a low-dimensional space. A linear transformation used to project new face images into the model space is divided into two sub-transformations: a rigid transformation of face images obtained through principal component analysis of face images and a non-rigid transformation responsible for preserving pair-wise distance relationships between face images. Also provided is a linear indexing method using the linear modeling method to perform the binning or algorithm-specific indexing task with little overhead.

US Patent:

8165352, Apr 24, 2012

Filed:

Aug 6, 2008

Appl. No.:

12/187028

Inventors:

Pranab Mohanty - Tampa FL, US
Sudeep Sarkar - Tampa FL, US
Rangachar Kasturi - Tampa FL, US

Assignee:

University of South Florida - Tampa FL

International Classification:

G06K 9/00

US Classification:

382115, 382118

Abstract:

A method of reconstructing biometric face image templates of a face recognition system (FRS) using the match scores or distances provided by the FRS. The match scores represent the distance between a image introduced to the FRS and the unknown image template stored in the FRS. The present method uses an affine transformation approximating the unknown algorithm within the FRS and the match scores provided by the FRS to determine the coordinates of the unknown target template. The coordinates of the unknown target template are then applied to a pseudo-inversion of the affine transformation to produce a reconstructed image template of the unknown target. This reconstructed image template can then be used to ‘break-in’ to the FRS.

US Patent:

20210030354, Feb 4, 2021

Filed:

Oct 19, 2020

Appl. No.:

17/073568

Inventors:

- Tampa FL, US
Dmitry Goldgof - Lutz FL, US
Rangachar Kasturi - Tampa FL, US
Terri Ashmeade - Tampa FL, US
Yu Sun - Tampa FL, US
Rahul Paul - Tampa FL, US
Md Sirajus Salekin - Tampa FL, US

International Classification:

A61B 5/00
A61B 5/1171
G06N 3/02

Abstract:

A Neonatal CNN (N-CNN) is provided for detecting neonatal pain emotion based upon facial recognition. A cascaded N-CNN is trained using a Neonatal Pain Assessment Database (NPAD) to automatically identify a neonatal patient experience pain in real-time. These results show that the automatic recognition of neonatal pain provided by the embodiments of the present invention is a viable and more efficient alternative to the current standard of pain assessment.

US Patent:

20190320974, Oct 24, 2019

Filed:

Apr 19, 2019

Appl. No.:

16/389513

Inventors:

Ghadh Alzamzmi - North Bethesda MD, US
Chih-Yun Pai - Tampa FL, US
Dmitry Goldgof - Lutz FL, US
Rangachar Kasturi - Tampa FL, US
Terri Ashmeade - Tampa FL, US
Yu Sun - Tampa FL, US

Assignee:

University of South Florida - Tampa FL

International Classification:

A61B 5/00

Abstract:

A system and method of automatically assessing pediatric and neonatal pain using facial expressions along with crying sounds, body movement, and vital signs change to improve the diagnosis and treatment of pain in the pediatric patient population.