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Ȩ Ȩ > ¿¬±¸¹®Çå > ¿µ¹® ³í¹®Áö > Journal of EEIS

Journal of EEIS

Current Result Document : 6 / 6 ÀÌÀü°Ç ÀÌÀü°Ç

ÇѱÛÁ¦¸ñ(Korean Title) Adaptive Data Association for Multi-Target Tracking using Relaxation
¿µ¹®Á¦¸ñ(English Title) Adaptive Data Association for Multi-Target Tracking using Relaxation
ÀúÀÚ(Author) Yang-Weon Lee   Hong Jeong  
¿ø¹®¼ö·Ïó(Citation) VOL 03 NO. 02 PP. 0267 ~ 0273 (1998. 04)
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(Korean Abstract)
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(English Abstract)
This paper introduces an adaptive algorithm determining the measurement-track association problem in multi-target tracking (MTT). We model the target and measurement relationships with mean field theory and then define a MAP estimate for the optimal association. Based on this model, we introduce an energy function defined over the measurement space, that incorporates the natural constraints for target tracking. To find the minimizer of the energy function, we derived a new adaptive algorithm by introducing the Lagrange multipliers and local dual theory. Through the experiments, we show that this algorithm is stable and works well in general environments. Also the advantages of the new algorithm over other algorithms are discussed.
Å°¿öµå(Keyword) Signal Processing   Data Association   Multi-Target Tracking   Relaxation  
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