CATS: A Color and Thermal Stereo Benchmark

no code implementations • CVPR 2017 • Wayne Treible, Philip Saponaro, Scott Sorensen, Abhishek Kolagunda, Michael O'Neal, Brian Phelan, Kelly Sherbondy, Chandra Kambhamettu

We present the Color And Thermal Stereo (CATS) benchmark, a dataset consisting of stereo thermal, stereo color, and cross-modality image pairs with high accuracy ground truth (< 2mm) generated from a LiDAR.

Stereo Matching Stereo Matching Hand

Robust Shape Registration using Fuzzy Correspondences

no code implementations • 18 Feb 2017 • Abhishek Kolagunda, Scott Sorensen, Philip Saponaro, Wayne Treible, Chandra Kambhamettu

We present a shape registration approach that solves for the transformation using fuzzy correspondences to maximize the overlap between the given shape and the target shape.

Material Classification With Thermal Imagery

no code implementations • CVPR 2015 • Philip Saponaro, Scott Sorensen, Abhishek Kolagunda, Chandra Kambhamettu

Typical algorithms use color and texture information for classification, but there are problems due to varying lighting conditions and diversity of colors in a single material class.

Classification General Classification +1