Philip Saponaro — accepted AI-conference papers

2017

CATS: A Color and Thermal Stereo Benchmark

Wayne Treible, Philip Saponaro, Scott Sorensen, Abhishek Kolagunda, Michael O'Neal, Brian Phelan +2

CVPR 2017spotlight

Stereo matching is a well researched area using visible-band color cameras. Thermal images are typically lower resolution, have less texture, and are noisier compared to their visible-band counterparts and are more challenging for stereo matching algorithms. Previous benchmarks for stereo matching e…

Cited by 75 PDF ↗Scholar ↗

2015

Material Classification With Thermal Imagery

Philip Saponaro, Scott Sorensen, Abhishek Kolagunda, Chandra Kambhamettu

CVPR 2015poster

Material classification is an important area of research in computer vision. 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. In this work we study the use of long wa…

Cited by 66 Source ↗PDF ↗Scholar ↗