A small object detection method based on local maxima and SSD

Abstract

Small object detection in complex scene is a difficult task in image processing. Normally, small objects in images are also weak objects where the contrast between targets and background is so subtle which makes it difficult to perceive. SSD(Single Shot MultiBox Detector) is one of the object detection method proved to be effective for normal size object detection, otherwise, unable to handle the small target task. A new small object detection method based on SSD is brought up in this paper. At first, a local maxima detector is performed in the image to obtain local maxima points in the image, which would be considered as the center of prior boxes for the subsequent object detection in feature maps of different levels. Secondly, the object extraction would be performed in con2_2 and conv3_3, that assures small objects does not be disappear in high level feature maps. Finally, a method to mark small object is brought up. The proposed method is performed in in several videos, which prove this method is feasible and effective.