The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Download
Publications Copernicus
Download
Citation
Articles | Volume XLII-2/W12
https://doi.org/10.5194/isprs-archives-XLII-2-W12-249-2019
https://doi.org/10.5194/isprs-archives-XLII-2-W12-249-2019
09 May 2019
 | 09 May 2019

ANIMAL DETECTION USING A SERIES OF IMAGES UNDER COMPLEX SHOOTING CONDITIONS

A. G. Zotin and A. V. Proskurin

Keywords: Animal Detection, Background Modeling, Camera Traps, MSR Algorithm

Abstract. Camera traps providing enormous number of images during a season help to observe remotely animals in the wild. However, analysis of such image collection manually is impossible. In this research, we develop a method for automatic animal detection based on background modeling of scene under complex shooting. First, we design a fast algorithm for image selection without motions. Second, the images are processed by modified Multi-Scale Retinex algorithm in order to align uneven illumination. Finally, background is subtracted from incoming image using adaptive threshold. A threshold value is adjusted by saliency map, which is calculated using pyramid consisting of the original image and images modified by MSR algorithm. Proposed method allows to achieve high estimators of animals detection.