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Michigan and ECE advancing computer vision at CVPR 2023

Look at some of the ways ECE and other University of Michigan researchers are using computer vision for real-world applications.

Live public street cams are tracking social distancing

Voxel51, a U-M startup led by Prof. Jason Corso, uses custom AI to continuously track vehicle, cyclist, and pedestrian traffic in real time at some of the most visited places in the world.

Creating a place where kids of all abilities can play together

Prof. Hun-Seok Kim helped design iGYM, an augmented reality system that allows disabled and able-bodied people to play physical games together.

Computer vision: Finding the best teaching frame in a video for fake video fightback

The frame in which a human marks out the boundaries of an object makes a huge difference in how well AI software can identify that object through the rest of the video.

Prof. Jason Corso on artificial intelligence

The most exciting use of AI for me focuses around a better collective use of our available resources, says Corso.

Paper award for training computer vision systems more accurately

PhD student Jean Young Song offers an improved solution to the problem of image segmentation.

Kyle Min awarded Towner Prize for Distinguished Academic Achievement

Kyle Min researches how computer vision can analyze law enforcement body cameras.

$1.6M toward artificial intelligence for data science

DARPA is trying to build a system that can turn large data sets into models that can make predictions, and U-M is in on the project.

COVE: a tool for advancing progress in computer vision

Centralizing available data in the intelligent systems community through a COmputer Vision Exchange for Data, Annotations and Tools, called COVE.

Bourne Pursuit: Improving computer tracking of human activity

Researchers have found a way to improve a computer’s human-tracking accuracy by looking at where the targets are going, but also at what they’re doing.

Silvio Savarese’s research applying computer vision techniques to construction sites leads to best paper award and a new spinoff company

“We have pioneered an integrated scene understanding framework that enables the automatic tracking of structural changes, allowing data to be collected easily.”

Computer Vision Course is part of a groundbreaking online initiative

Computer Vision seeks to imitate humans’ ability to recognize objects, navigate scenes, reconstruct layouts, and understand the geometric space and semantic meaning.

Srinath Sridhar awarded Rackham International Student Fellowship

Srinath’s research focuses on using computer vision techniques such as markerless camera tracking for creating augmented reality AR environments.

Sid Bao earns Best Student Paper Award for Computer Vision Research

Bao’s research is in Semantic Structure from Motion, a new framework for jointly recognizing objects as well as reconstructing their underlying 3D geometry.

Silvio Savarese authors book in the field of Computer Vision

“This book organizes and introduces major concepts in 3D scene and object representation and inference from still images.”

Computer Vision Research Recognized at Innovation in AEC Conference

With D4AR models, you can monitor progress, productivity, safety, quality, constructability and even site logistics remotely.