Insect Identification for Environmental Monitoring and Ecological Science

The goal of this project is to develop robotic technology and computer vision algorithms for automating biodiversity surveys of small arthropods including (a) macroinvertebrates in freshwater streams, (b) soil mesofauna, and (c) freshwater zooplankton. Under a 4-year ITR grant from NSF, we developed robotic apparatus and computer vision methods for classifying stoneflies to the level of genus. We recently obtained another NSF grant to extend this work to handle soil mesofauna and freshwater zooplankton.

Team members

Thomas G. Dietterich (PI); Machine Learning
Dave Lytle (co-PI); Fresh water entomologist
Andy Moldenke (co-PI); Entomologist for soil mesofauna
Linda Shapiro (co-PI); Pattern recognition and computer vision
Bob Paasch (co-PI); Mechanical Design
Eric Mortensen (co-PI); Computer vision and pattern recognition
Wei Zhang. Computer vision and machine learning graduate student (Dietterich).
Nadia Payet. Computer vision graduate student (Mortensen).
Natalia Larios. Computer vision and machine learning graduate student (Shapiro).

One of our edible specimens:

Current Status

Stoneflies

Soil Mesofauna

Publications

Peterson, C., Paasch, R. K., Ge, P., Dietterich, T. G. (2007). Product innovation for interdisciplinary design under changing requirements. International Conference on Engineering Design (ICED2007), Paris, France. PDF preprint.

E. N. Mortensen, E. L. Delgado, H. Deng, D. Lytle, A. Moldenke, R. Paasch, L. Shapiro, P. Wu, W. Zhang, T. G. Dietterich (2007). Pattern Recognition for Ecological Science and Environmental Monitoring: An Initial Report. In N. MacLeod and M. O'Neill (Eds.) Algorithmic Approaches to the Identification Problem in Systematics. PDF preprint.

Deng, H., Zhang, W., Mortensen, E., Dietterich, T. (2007). Principal Curvature-based Region Detector for Object Recognition. IEEE Conference on Computer Vision and Pattern Recognition (CVPR-2007). Minneapolis, MN. PDF Preprint.

Larios, N., Deng, H., Zhang, W., Sarpola, M., Yuen, J., Paasch, R., Moldenke, A., Lytle, D., Ruiz Correa, S., Mortensen, E., Shapiro, L., Dietterich, T. (2007). Automated Insect Identification through Concatenated Histograms of Local Appearance Features. Machine Vision and Applications. PDF Preprint.

Larios, N., Deng, H., Zhang, W., Sarpola, M., Yuen, J., Paasch, R., Moldenke, A., Lytle, D., Ruiz Correa, S., Mortensen, E., Shapiro, L. G., Dietterich T. G. (2007). Automated Insect Identification through Concatenated Histograms of Local Appearance Features. IEEE Workshop on Applications of Computer Vision (WACV-2007), 26-32. Austin, TX. PDF Preprint.

Deng, H., Mortensen, E. N., Shapiro, L., Dietterich, T. G. (2006). Reinforcement Matching Using Region Context. In S. Lucey and T. Chen (Eds.) Beyond Patches. Workshop at IEEE Conference on Computer Vision and Pattern Recognition. IEEE. New York. PDF preprint.

Zhang, W., Deng, H., Dietterich, T. G., Mortensen, E. N. (2006). A Hierarchical Object Recognition System Based on Multi-scale Principal Curvature Regions. Proceedings of the International Conference on Pattern Recognition, Vol. I. 778-782. PDF Preprint.

Presentations

Dietterich, T. (2007). BugID: Rapid Throughput Insect Population Counting Using Computer Vision. PDF of Powerpoint Presentation.

Acknowledgement of Financial Support

Support for this project is provided by the National Science Foundation under NSF Grant numbers IIS-0326052 and IIS-0705765. Any opinions, findings and conclusions or recomendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation (NSF).