Multiple hypothesis tracking in microscopy images
ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
Multiple hypothesis tracking in cluttered condition
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Tracking aircrafts by using impulse exclusive filter with RBF neural networks
TAINN'05 Proceedings of the 14th Turkish conference on Artificial Intelligence and Neural Networks
Data association and geolocation for electronic support systems
Computers and Electrical Engineering
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A concept of target perceivability is introduced, which is related to such concepts as target existence and target observability. Its probability provides a basis for an integrated approach to track initiation, confirmation, termination, and refinement of track maintenance algorithms. This paper proposes the concepts of target perceivability and presents a recursion of its probability based on hidden Markov models (HMMs) and their applications to tracker analysis, development, and design, in particular, in the context of the probabilistic data association (PDA) method. Specifically, several important quantities and track life are analyzed; a perceivability-based probabilistic approach to track confirmation and termination is proposed; two versions of perceivability-based PDA trackers are presented. Simulation results are provided to demonstrate their performance