A Comprehensive Review Towards Appropriate Feature Selection for Moving Object Detection Using Aerial Images

Abstract

Efficient feature extraction for moving object using aerial images is still an unsolved issue in computer vision, image processing and pattern recognition research domains. Aerial types of images contain various environmental constraints due to capture frames from various altitudes level, i.e. illumination, shadows, occlusion. For this reason, appropriate feature selection for those types of images needs more attention by the researchers to improve detection rate with fast and computationally less complex features extraction method. This research performed comprehensive review with critical analysis for using various features with various methods for moving object detection using aerial images. In this context, three aspects for critical analysis of using various features are identified followed by challenges of using various features. After that, existing methods with advantages and barriers are comprehensively described with various constraints claimed by the previous research. Next, justification for the need of new feature selection is elaborated for optimum detection performance. Later, adequate validation matrics are illustrated to evaluate various features based moving object detection using aerial images performed in the previous research. The overall review performed in this paper have been comprehensively studied and expected to contribute significantly in computer vision, image processing pattern recognition research field.