Staff R&D Engineer
Eric Smith joined Kitware in 2011 as a Research and Development Engineer on the Computer Vision team. He holds a Ph.D. in Computer Vision from Rensselaer Polytechnic Institute, where he also received his B.S. in Computer Science. Dr. Smith’s graduate research focused on the automatic registration of combined image/LiDAR scans. He developed a pairwise registration algorithm designed to handle scan pairs suffering from low overlap, changes, intensity differences, and wide viewpoint differences. Dr. Smith has also worked on feature detection, description, and matching algorithms targeted at coarse alignment for combined image/LiDAR scans. He has also developed a fully automatic multiple scan registration algorithm. He has published three computer vision papers and has reviewed papers for PAMI, IVC, and ICRA.
Dr. Smith’s recent research at Kitware has been on deep learning for object detection. He is a key contributor to MAP-Tk focusing on real time feature matching and GPU acceleration. He has also worked on dense depth estimation from video, super resolution, and camera trajectory tracking in medical applications.
- C. Long, E. Smith, A. Basharat, and A. Hoogs, "A C3D-based convolutional neural network for frame dropping detection in a single video shot," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshop on Media Forensics, 2017. [URL]
- J. Moeller, E. Smith, A. Basharat, M. Turek, A. Hoogs, and E. Blasch, "Automatic pattern of life learning in satellite images through graph kernels," in Proceedings of the MSS National Symposium on Sensor and Data Fusion, 2017.
- M. Leotta, E. Smith, M. Dawkins, and P. Tunison, "Open source structure-from-motion for aerial video," in Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2016. [URL]
- E. Smith, R. Radke, and C. Stewart, "Physical Scale Keypoints: Matching and Registration for Combined Intensity/Range Images," International Journal of Computer Vision, vol. 97, no. 1, pp. 2-17, Mar. 2012. [URL]
- E. Smith, "Registration of combined range-intensity scans," Ph.D. dissertation, Rensselaer Polytechnic Institute, 2012.
- E. R Smith, R. Radke, and C. Stewart, "Physical Scale Intensity-Based Range Keypoints," in Proceedings of the International Symposium on 3D Data Processing, Visualization, and Transmission, 2010.
- E. Smith, B. King, C. Stewart, and R. Radke, "Registration of combined range–intensity scans: Initialization through verification," Computer Vision and Image Understanding, vol. 110, no. 2, pp. 226-244, May 2008. [URL]