Detection of pollen bearing honey bees in hive entrance images

Automatic detection of pollen bearing honey bees can provide information important both for pollination monitoring and for assessing health and strength of a beehive. In this paper we analyze some of the methods for detection of pollen bearing honey bees in images obtained at hive entrance. The proposed approach is divided into two parts. In the first part we segment honey bees from images. To this end we analyze two segmentation methods based on color descriptors. Then in the second part we use these segmented regions to classify the bees into two classes with or without pollen. Classification is conducted using SVMs trained on few variations of VLAD-encoded SIFT descriptors. On a dataset of images acquired at the hive entrance, we obtain 0.7971 IoU score for segmentation, and 0.9150 AUC score for classification.