Jason J. Corso
Associate Professor
Electrical Engineering
and Computer Science

University of Michigan
Email: jjcorso@eecs.umich.edu
Office: 4227 EECS
Phone: 734-647-8833
Bio: [txt]
Vita: [pdf]
Hours: T 1350-1450
R 1100-1200
by appt.
Cal: Availability

Index Page Anchors
Selected Publications
Code and Data
Current Grants
Professional Service

Publication Tag Cloud
active clustering  activity recognition  artificial intelligence  augmented reality  belief propagation  bioinformatics  biomarkers  biometrics  braintumor  cognitive systems  computational finance  computer forensics  computer graphics  computer vision  computer-aided diagnosis  cosegmentation  data mining  deformable  dictionary transfer  digitial humanities  document imaging  domain adaptation  dynamic linear models  endoscopy  evaluation  event recognition  facade detection  face detection  face recognition  feature extraction  fusion  gesture recognition  gpu  grammar  graph cuts  graph-based  graphical models  haptics  hierarchical  higher-order  human pose estimation  human-computer interaction  image denoising  image processing  image retrieval  image understanding  language grounding  localization  lung imaging  machine learning  mapping  max-margin  medical imaging  metric learning  mobile robotics  mosaicking  motion estimation  mrf  multimedia  natural language  navigation  neuroimaging  object detection  ontology  probabilistic ontology  protein structure prediction  random forest  reconstruction  segmentation  semantic segmentation  slam  spectral clustering  spine imaging  stereo  streaming  supervoxel  surgical robotics  tomographic reconstruction  tracking  video summarization  video to text  video understanding  visual psychophysics  volume rendering  voxel maps 

Dr. Jason J. Corso is currently an Associate Professor of Electrical Engineering and Computer Science at the University of Michigan. He received his Ph.D. in Computer Science at The Johns Hopkins University in 2005. He is a recipient of the NSF CAREER award (2009), ARO Young Investigator award (2010), Google Faculty Research Award (2015) and on the DARPA CSSG.

His main research thrust is high-level computer vision and its relationship to human language, robotics and data science. He primarily focuses on problems in video understanding such as video segmentation, activity recognition, and video-to-text. From biomedicine to recreational video, imaging data is ubiquitous. Yet, imaging scientists and intelligence analysts are without an adequate language and set of tools to fully tap the information-rich image and video. He works to provide such a language; specifically, he primarily studies the coupled problems of segmentation and recognition from a Bayesian perspective emphasizing the role of statistical models in efficient visual inference. His long-term goal is a comprehensive and robust methodology of automatically mining, quantifying, and generalizing information in large sets of projective and volumetric images and video.

More information on these topics can be found in the research pages.

Selected Publications     [complete list here]
[1] C. Xu and J. J. Corso. Actor-action semantic segmentation with grouping-process models. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2016. [ bib | data ]
[2] V. Dhiman, Q.-H. Tran, J. J. Corso, and M. Chandraker. A continuous occlusion model for road scene understanding. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2016. [ bib ]
[3] D. M. Johnson, C. Xiong, and J. J. Corso. Semi-supervised nonlinear distance metric learning via forests of max-margin cluster hierarchies. IEEE Transactions on Knowledge and Data Engineering, 28(4):1035--1046, 2016. [ bib | DOI | .pdf ]
[4] W. Chen and J. J. Corso. Action detection by implicit intentional motion clustering. In Proceedings of IEEE International Conference on Computer Vision, 2015. [ bib | poster | .pdf ]
[5] C. Xu, S.-H. Hsieh, C. Xiong, and J. J. Corso. Can humans fly? Action understanding with multiple classes of actors. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2015. [ bib | poster | data | .pdf ]
[6] J. Lu, R. Xu, and J. J. Corso. Human action segmentation with hierarchical supervoxel consistency. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2015. [ bib | .pdf ]
[7] R. Xu, C. Xiong, W. Chen, and J. J. Corso. Jointly modeling deep video and compositional text to bridge vision and language in a unified framework. In Proceedings of AAAI Conference on Artificial Intelligence, 2015. [ bib | .pdf ]
[8] S. Kumar, V. Dhiman, and J. J. Corso. Learning compositional sparse models of bimodal percepts. In Proceedings of AAAI Conference on Artificial Intelligence, 2014. [ bib | code | .pdf ]
[9] W. Chen, C. Xiong, R. Xu, and J. J. Corso. Actionness ranking with lattice conditional ordinal random fields. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2014. [ bib | poster | code | .pdf ]
[10] V. Dhiman, A. Kundu, F. Dellaert, and J. J. Corso. Modern MAP inference methods for accurate and faster occupancy grid mapping on higher order factor graphs. In Proceedings of International Conference on Robotics and Automation, 2014. [ bib | code | .pdf ]
[11] C. Xiong, W. Chen, G. Chen, D. Johnson, and J. J. Corso. Adaptive quantization: An information-based approach to learning binary codes. In Proceedings of SIAM International Conference on Data Mining, 2014. [ bib | code | .pdf ]
[12] C. Xu, R. F. Doell, S. J. Hanson, C. Hanson, and J. J Corso. A study of actor and action semantic retention in video supervoxel segmentation. International Journal of Semantic Computing, 2014. Selected as a Best Paper from ICSC; an earlier version appeared as arXiv:1311.3318. [ bib | .pdf ]
[13] C. Xu, S. Whitt, and J. J. Corso. Flattening supervoxel hierarchies by the uniform entropy slice. In Proceedings of the IEEE International Conference on Computer Vision, 2013. [ bib | poster | project | video | .pdf ]
[14] V. Dhiman, J. Ryde, and J. J. Corso. Mutual localization: Two camera relative 6-dof pose estimation from reciprocal fiducial observation. In Proceedings of International Conference on Intelligent Robots and Systems, 2013. [ bib | slides | code | .pdf ]
[15] P. Das, C. Xu, R. F. Doell, and J. J. Corso. A thousand frames in just a few words: Lingual description of videos through latent topics and sparse object stitching. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2013. [ bib | poster | data | .pdf ]
[16] P. Das, R. K. Srihari, and J. J. Corso. Translating related words to videos and back through latent topics. In Proceedings of Sixth ACM International Conference on Web Search and Data Mining, 2013. [ bib | .pdf ]
[17] C. Xu, C. Xiong, and J. J. Corso. Streaming hierarchical video segmentation. In Proceedings of European Conference on Computer Vision, 2012. [ bib | code | project | .pdf ]
[18] C. Xiong, D. Johnson, R. Xu, and J. J. Corso. Random forests for metric learning with implicit pairwise position dependence. In Proceedings of ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012. [ bib | slides | code | .pdf ]
[19] S. Sadanand and J. J. Corso. Action bank: A high-level representation of activity in video. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2012. [ bib | code | project | .pdf ]

Code and Data Downloads
Video2Text.net: A website and web-service for automatic conversion of videos to natural language sentences based on the video content. This website showcases our work in the vision+language domain.

YouCook data set: 88 challenging videos of various cooking (third-person viewpoint, different backgrounds, dynamic camera and person movement) with natural language annotations (about 8 per video) and object and action annotations. Includes a benchmark ROUGE scoring evaluation. The data set was published with our CVPR 2013 paper.

Hierarchy Agreement Index: implementation of our AAAI LBP 2013 cross-hierarchy evaluation tool for general use.

Random Forest Distance -- tree-structured metric learning that implicitly adapts the metric over the sample space based on our KDD 2012 paper. (Code updated 2/28/14)

Action Bank full code and processed data sets  [direct link to code]

LIBSVX: A Supervoxel Library and Benchmark for Early Video Processing. Implements a suite of supervoxel video segmentation methods as well as a quantitative set of 2D and 3D metrics for good supervoxels.

Graph-Shifts Code (Java) and example data.

Video label propagation code and benchmark data set.

UB/College Park stereo building facade dataset. [more information].

ARO YIP (PI): GBS: Guidance By Semantics-Using High-Level Visual Inference to Improve Vision-based Mobile Robot Localization
NSF CAREER (PI): CAREER: Generalized Image Understanding with Probabilistic Ontologies and Dynamic Adaptive Graph Hierarchies
DARPA MINDSEYE (PI): ISTARE: Intelligent Spatio-Temporal Activity Reasoning Engine

Recently Expired Grants

DARPA CSSG-III (PI): Transferring ACE to the Analyst
FHWA (CUBRC Sub) (PI): Computer Vision and Mobile Robot Technologies for Advanced Emergency Response
IARPA ALADDIN (Kitware Sub) (PI): Ontology, Event Agents and Event Recounting for ALADDIN
NIH (HRI Sub) (PI): Objective Imaging-Based Assessment of Smoking Behavior from Used Filters
DARPA CSSG-II (PI): ACE -- Active Clustering for Exploitation and Defense Forensics
Naval PS (PI): Comprehensive Object Detection Library for Large-Scale Image Analytics
ARO DURIP (PI): Two-Rank Mobile Robot Fleet for Swarm Surveillance, WarFighter Assistance, and other Army-related Research and Research-Related Education
CIA (PI): Semantic Video Summarization With Ontology-Driven Probabilistic Inference on Massive Multimedia Collections

Professional Service
Editorial Board: International Journal of Computer Vision 2014-Current
Associate Editor: IEEE Transactions on Pattern Analysis and Machine Intelligence 2014-Current
Associate Editor: Computer Methods and Programs in Biomedicine 2009-2014
Area Chair/Senior PC: AAAI 2016,   AAAI 2017,   CVPR 2012,  CVPR 2013,   WACV 2014,   ECCV 2014,   ICCV 2015,   ICRA 2015 (AE), ICRA 2016 (AE; Best AE Award)
Program Committee/Reviewer:
     CVPR 2003  2006  2007  2009  2010  2011  2014  2015  2016 
     ECCV  2006  2010  2012 
     EMMCVPR  2007  2009  2011  2013 
     ICCV  2007  2009  2013
     ICRA  2005  2009  2011  2012  2013
     IROS  2007  2012;  2013 
     MICCAI  2003,   2006  2007  2008  2009  2012  2013 

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last updated: Fri Sep 16 09:34:49 2016; copyright jcorso
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