TR2010-018
Needle Picking: A Sampling Based Track-Before-Detection Method for Small Targets
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- "Needle Picking: A Sampling Based Track-before-Detection Method for Small Targets", SPIE Conference on Signal and Data Processing of Small Targets, DOI: 10.1117/12.850452, April 2010, vol. 7698.BibTeX TR2010-018 PDF
- @inproceedings{Porikli2010apr,
- author = {Porikli, F.M.},
- title = {Needle Picking: A Sampling Based Track-before-Detection Method for Small Targets},
- booktitle = {SPIE Conference on Signal and Data Processing of Small Targets},
- year = 2010,
- volume = 7698,
- month = apr,
- doi = {10.1117/12.850452},
- url = {https://www.merl.com/publications/TR2010-018}
- }
,
- "Needle Picking: A Sampling Based Track-before-Detection Method for Small Targets", SPIE Conference on Signal and Data Processing of Small Targets, DOI: 10.1117/12.850452, April 2010, vol. 7698.
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Research Area:
Abstract:
We present a computationally efficient track-before-detect algorithm that achieves more than 50% true detection at 0.000001 false alarm rate for pixel sized unknown number of multiple targets when the signal-to-noise ratio is less than 7dB. Without making any assumptions on the distribution functions, we select a small number of cells, so called as needles, and generate motion hypotheses using the target state transition model. We accumulate cell likelihoods along each hypothesis in the temporal window and append the accumulated values to the corresponding queues of the cell position in the most recent image. We assign a target in case the queue maximum is greater than a threshold that produces the specified false alarm rate.
Related News & Events
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NEWS SPIE Conference on Signal and Data Processing of Small Targets 2010: publication by MERL researchers and others Date: April 15, 2010
Where: SPIE Conference on Signal and Data Processing of Small Targets
Research Area: Computer VisionBrief- The paper "Needle Picking: A Sampling Based Track-before-Detection Method for Small Targets" by Porikli, F.M. was presented at the SPIE Conference on Signal and Data Processing of Small Targets.