Format

Send to

Choose Destination
J Vis Exp. 2014 Oct 15;(92):e52111. doi: 10.3791/52111.

Flying insect detection and classification with inexpensive sensors.

Author information

1
Department of Computer Science and Engineering, University of California, Riverside; ychen053@ucr.edu.
2
Department of Entomology, University of California, Riverside.
3
Institute of Mathematics and Computer Sciences, University of São Paulo - USP.
4
ISCA Technologies.
5
Department of Computer Science and Engineering, University of California, Riverside.

Abstract

An inexpensive, noninvasive system that could accurately classify flying insects would have important implications for entomological research, and allow for the development of many useful applications in vector and pest control for both medical and agricultural entomology. Given this, the last sixty years have seen many research efforts devoted to this task. To date, however, none of this research has had a lasting impact. In this work, we show that pseudo-acoustic optical sensors can produce superior data; that additional features, both intrinsic and extrinsic to the insect's flight behavior, can be exploited to improve insect classification; that a Bayesian classification approach allows to efficiently learn classification models that are very robust to over-fitting, and a general classification framework allows to easily incorporate arbitrary number of features. We demonstrate the findings with large-scale experiments that dwarf all previous works combined, as measured by the number of insects and the number of species considered.

PMID:
25350921
PMCID:
PMC4541473
DOI:
10.3791/52111
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for MyJove Corporation Icon for PubMed Central
Loading ...
Support Center