Title :
Comments on "Joint Detection and Estimation of Multiple Objects From Image Observations
Author :
Davey, Samuel J.
Author_Institution :
Intell. Surveillance & Reconnaissance Div., Defence Sci. & Technol. Organ., Edinburgh, SA, Australia
fDate :
3/1/2012 12:00:00 AM
Abstract :
The above article [1] introduced an algorithm for multitarget track-before-detect based on a multi-Bernoulli random finite set model (MB-TBD). This new algorithm was compared with the Histogram Probabilistic Multi-Hypothesis Tracker (H-PMHT) on simulated data examples containing multiple targets with non-linear dynamics. The authors reported poor performance from H-PMHT and described several deficiencies of the algorithm. This note highlights unnecessary assumptions made in the assessment of H-PMHT and repeats two of the simulation examples after relaxing them. We demonstrate a substantial improvement in performance compared with the originally published results. The simulation example is also shown to be a relatively high signal to noise problem and good performance is obtained from a conventional detect-then-track algorithm.
Keywords :
image processing; H-PMHT; histogram probabilistic multi-hypothesis tracker; image observations; joint detection; joint estimation; multiBernoulli random finite set model; target track-before-detect; Approximation algorithms; Estimation; Heuristic algorithms; Target tracking;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2011.2173679