Fully-Automatic Target Detection and Tracking for Real-Time, Airborne Imaging Applications

Autor:	Sinan Oz, Tunc Alkanat, Emre Tunali
Rok vydání:	2016
Předmět:	Maximally stable extremal regions Computer science business.industry Detector Kernel density estimation ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Scale invariance Temporal consistency Compact space Fully automatic Canny edge detector Computer vision Artificial intelligence business
Zdroj:	Communications in Computer and Information Science ISBN: 9783319299709 VISIGRAPP (Selected Papers)
Popis:	In this study, an efficient, robust algorithm for automatic target detection and tracking is introduced. Procedure starts with a detection phase. Proposed method uses two alternatives for the detection phase, namely maximally stable extremal regions detector and Canny edge detector. After detection, regions of interest are evaluated and eliminated according to their compactness and effective saliency. The detection process is repeated for a predetermined number of pyramid levels where each level processes a downsampled version of input image to achieve scale invariance. Then, temporal consistency for detections from all scales is evaluated and target likelihood map is constructed using kernel density estimation in order to merge all target hypotheses. Finally, outstanding targets are selected from target likelihood map and tracking is achieved by minimizing spatial distance between the selected targets in consecutive frames.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::86d3df2f4fa911f97b3509ebf8befe97 https://doi.org/10.1007/978-3-319-29971-6_13 Zobrazit plný text záznamu