Patent · US Active

Deep multi-task learning framework for face detection, landmark localization, pose estimation, and gender recognition

US10860837B2 · kind B2 · utility

5Cited by

12References

8Claims

0Family size

Assignee

UNIVERSITY OF MARYLAND, COLLEGE PARK · US

Inventors

Rajeev Ranjan · College Park, US
Vishal M. Patel · Silver Spring, US
Ramalingam Chellappa · Potomac, US
Carlos Castillo · Seattle, US

Key dates

Filing date	Jul 20, 2016
Grant date	Dec 8, 2020
Priority date	—
Expiry date	Jul 20, 2036

Classification

Technology area (CPC G)Physics
CPC primaryG06V10/993
WIPO fieldComputer technology
WIPO sectorElectrical engineering

Abstract

Various image processing may benefit from the application deep convolutional neural networks. For example, a deep multi-task learning framework may assist face detection, for example when combined with landmark localization, pose estimation, and gender recognition. An apparatus can include a first module of at least three modules configured to generate class independent region proposals to provide a region. The apparatus can also include a second module of the at least three modules configured to classify the region as face or non-face using a multi-task analysis. The apparatus can further include a third module configured to perform post-processing on the classified region.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.