CIVA
The Computational Imaging and Visualization Analysis lab is in the Department of Computer Science at the University of Missouri and collaboratively develops algorithms, tools and software for quantifying visual information and facilitating discoveries in STEMM. CIVA conducts research on computational aspects of computer vision, image processing, visualization, algorithm parallelization, high performance computing, machine learning and mathematical methods for image & video understanding. Application areas center around wide area motion imagery, full motion video for defense biometrics. In the biological and biomedical areas we are focused on multiscale systems biology and phenomics from sub-cellular to tissue scale analysis for understanding function and disease processes. Our research has been funded by DoD, NIH, NSF, NASA and NGA.
In the news
Small satellites (sats) e.g., cube sats, are poised to revolutionize Earth observations from space. Large constellations of small sats offer particular advantages compared to traditional (larger) imaging satellites, such as higher temporal resolution (image sequences and revisit times) system resiliency and agility, and the potential for big savings in life-cycle costs. A panel on discussion on this will consider how the small sat revolution may play out for the remote sensing community writ large. SPIE 2016
In the news
Organized workshop on Video Summarization for Large-scale Analytics at ICCV 2015
In the news
Our novel flux tensor with split gaussian (FTSG) hybrid moving object detection system won the CVPR 2014 Change Detection Workshop ranking first among nearly twenty state-of-the-art algorithms. The FTSG method was tested on 53 challenging videos and is robust to changes in illumination, precipitation, camera jitter, low frame rate, night time, static objects, removed objects and thermal turbulence. movie
In the news
Camera-equipped, autonomous, unmanned aerial vehicles (UAVs) can fly low to the ground and take high-resolution images of crops that tell farmers exactly where to plant their seeds or add fertilizers—at a tenth the cost of flying a plane or purchasing satellite images. Article
In the news
This graphical image encoding bacterial swarming motion was created by Filiz Bunyak and Kannappan Palaniappan at the University of Missouri-Columbia in collaboration with Mingzhai Sun and Joshua Shaevitz of Princeton's Department of Physics and the Lewis-Sigler Institute for Integrative Genomics.
NBC/Art of Science slideshow, slide #5.
Kolam
Kolam is a tool to visualize large datasets, notably biomedical and geospatial imagery.
Firefly
Firefly is a web based tool for image analysis, tracking, and segmentation. It supports different annotation types such as point, lines, polygons, and ploylines. It interacts with a database on a webserver to provide an interactive platform for visualizing and editing tracking data.
Fall 2017
The group picture by the columns