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

Daniel Moreira

Graduate Students

Sreya Banerjee

Nathaniel Blanchard

Katherine Finley (co-advised with Patrick Flynn)

Samuel Grieggs

Jeffrey Kinnison

Brandon RichardWebster

Ali Shahbazi

Bingyu Shen

Rosaura Vidal Mata

Teaching

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. "Neuron Segmentation Using Deep Complete Bipartite Networks,"
    Jianxu Chen, Sreya Banerjee, Abhinav Grama, Walter J. Scheirer, Danny Z. Chen,
    Proceedings of the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI),
    September 2017.
  2. "The Extreme Value Machine,"
    Ethan Rudd, Lalit P. Jain, Walter J. Scheirer, Terrance Boult,
    IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI),
    Accepted for Publication April 2017.
  3. "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.
  4. "Extreme Value Theory-Based Methods for Visual Recognition,"
    Walter J. Scheirer,
    Morgan & Claypool Publishers,
    February 2017.
  5. "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.
  6. "Reconstruction of Genetically Identified Neurons Imaged by Serial-Section Electron Microscopy,"
    Maximilian Joesch, David Mankus, Masahito Yamagata, Ali Shahbazi, Richard Schalek, Adi
    Suissa-Peleg
    , Markus Meister, Jeff W. Lichtman, Walter J. Scheirer, Joshua R. Sanes,
    eLife,
    July 2016.
  7. "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.
  8. "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.

New Research in arXiv

  1. "Spotting the Difference: Context Retrieval and Analysis for Improved Forgery Detection
    and Localization,"
    Joel Brogan, Paolo Bestagini, Aparna Bharati, Allan Pinto, Daniel Moreira, Kevin Bowyer,
    Patrick Flynn, Anderson Rocha, Walter J. Scheirer,
    May 2017.
  2. "Using Human Brain Activity to Guide Machine Learning,"
    Ruth C. Fong, Walter J. Scheirer, David D. Cox,
    March 2017.
  3. "PsyPhy: A Psychophysics Driven Evaluation Framework for Visual Recognition,"
    Brandon RichardWebster, Samuel E. Anthony, Walter J. Scheirer,
    November 2016.

Recent Projects (see all)

Tools for Neuroscience

Tools for Neuroscience

Fall 2015 - Present

Techniques to help neuroscientists understand neuroanatomy and function

Keywords: connectomics, electron microscopy, two-photon imaging, x-ray tomography, 3D reconstruction
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

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)

Activities