Research Overview

My research is primarily focused around the problem of recognition, including the representations and algorithms supporting solutions to it. I am particularly interested in features and learning-based methods that apply to both vision and language, thus breaking away from the persistent compartmentalization of recognition tasks (something hinted at by David Marr over 30 years ago). This has led to some interesting, and often unconventional approaches that can be applied to a broad set of areas including computer vision, machine learning, human biometrics, and the digital humanities. Specifically, my work is looking at open set recognition, extreme value theory models for visual recognition, biologically-inspired learning algorithms, and stylometry.

Walter J. Scheirer

Curriculum Vitae

PDF Format

Postdoctoral Fellows

Christopher W. Forstall

Daniel Moreira

Graduate Students

Sreya Banerjee

Nathaniel Blanchard

Katherine Finley (co-advised with Patrick Flynn)

Jeffrey Kinnison

Brandon RichardWebster

Ali Shahbazi

Bingyu Shen

Rosaura Vidal Mata


Spring 2017: CSE 40567/60567 Computer Security

Spring 2016: CSE 40567/60567 Computer Security

Fall 2015: CSE 40537/60537 Biometrics

Recent Publications (see all)

  1. "Predicting First Impressions with Deep Learning,"
    Mel McCurie, Fernando Beletti, Lucas Parzianello, Allen Westendorp, Samuel E. Anthony,
    Walter J. Scheirer,
    Proceedings of the IEEE Conference on Automatic Face and Gesture Recognition (FG),
    May 2017.
  2. "Extreme Value Theory-Based Methods for Visual Recognition,"
    Walter J. Scheirer,
    Morgan & Claypool Publishers,
    February 2017.
  3. "Authorship Attribution for Social Media Forensics,"
    Anderson Rocha, Walter J. Scheirer, Christopher W. Forstall, Thiago Cavalcante, Antonio Theophilo,
    Bingyu Shen
    , Ariadne R. B. Carvalho, Efstathios Stamatatos,
    IEEE Transactions on Information Forensics and Security (T-IFS),
    January 2017.
  4. "Reconstruction of Genetically Identified Neurons Imaged by Serial-Section Electron Microscopy,"
    Maximilian Joesch, David Mankus, Masahito Yamagata, Ali Shahbazi, Richard Schalek, Adi
    , Markus Meister, Jeff W. Lichtman, Walter J. Scheirer, Joshua R. Sanes,
    July 2016.
  5. "The Sense of a Connection: Automatic Tracing of Intertextuality by Meaning,"
    Walter J. Scheirer, Christopher W. Forstall, Neil Coffee,
    Digital Scholarship in the Humanities (DSH),
    April 2016.
  6. "Open Set Fingerprint Spoof Detection Across Novel Fabrication Materials,"
    Ajita Rattani, Walter J. Scheirer, Arun Ross,
    IEEE Transactions on Information Forensics and Security (T-IFS),
    November 2015.
  7. "Probability Models for Open Set Recognition,"
    Walter J. Scheirer, Lalit P. Jain, Terrance E. Boult,
    IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI),
    November 2014.
  8. "Multi-Class Open Set Recognition Using Probability of Inclusion,"
    Lalit P. Jain, Walter J. Scheirer, Terrance E. Boult,
    Proceedings of the European Conference on Computer Vision (ECCV),
    September 2014.
  9. "Perceptual Annotation: Measuring Human Vision to Improve Computer Vision,"
    Walter J. Scheirer, Samuel E. Anthony, Ken Nakayama, David D. Cox,
    IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI),
    August 2014.

New Research in arXiv

  1. "Using Human Brain Activity to Guide Machine Learning,"
    Ruth C. Fong, Walter J. Scheirer, David D. Cox,
    March 2017.
  2. "PsyPhy: A Psychophysics Driven Evaluation Framework for Visual Recognition,"
    Brandon RichardWebster, Samuel E. Anthony, Walter J. Scheirer,
    November 2016.

Recent Projects (see all)

Visual Place Recognition

Visual Place Recognition

Spring 2013 - Present

Condition invariant visual place recognition for robot navigation inspired by vision science

Keywords: robotics, navigation, place recognition, whole image matching, patch matching, calibration
Is good recognition metric?

Good Recognition is Non-metric

Fall 2012 - Spring 2014

A new look at a fundamental question in computer vision: is recognition metric?

Keywords: machine learning, metric learning, recognition, face recognition, object recognition

Psychophysics for Computer Vision

Fall 2012 - Present

Measuring exemplar-by-exemplar dif´Čüculty and the pattern of errors of humans for supervised learning

Keywords: machine learning, psychology, citizen science, psychophysics, face detection, attributes
Open Set Recognition

Open Set Recognition

Spring 2011 - Present

Theory and algorithms that address the difficult problem of training without complete class knowledge

Keywords: machine learning, object recognition, face recognition, support vector machines, 1-vs-set machine
Extreme Value Theory for Visual Recognition

Extreme Value Theory for Visual Recognition

Spring 2008 - Present

The theory and practice of recognition score analysis for prediction and fusion

Keywords: calibration, meta-recognition, score analysis, object recognition, face recognition, attributes
Language and Literature

Language & Literature

Spring 2009 - Present

Machine learning and related statistical methods to improve the process by which intertextuality is studied

Keywords: computational linguistics, intertextuality, sound, stylistics, classics, authorship attribution
Digital Image and Video Forensics

Digital Image and Video Forensics

Spring 2008 - Present

Approaches to steganalysis, forgery detection and sensor fingerprinting

Keywords: forensics, forgery detection, data hiding, source identification, sensor fingerprinting

Recent Talks (see all)