Skip to Main content Skip to Navigation
Conference papers

Trade-off between GPGPU based implementations of multi object tracking particle filter

Abstract : In this work, we present the design, analysis and implementation of a decentralized particle filter (DPF) for multiple object tracking (MOT) on a graphics processing unit (GPU). We investigate two variants of the implementation , their advantages and caveats in terms of scaling with larger particle numbers and performance on several datasets. First we compare the precision of our GPU implementation with standard CPU version. Next we compare performance of the GPU variants under different scenarios. The results show the GPU variant leads to a five fold speedup on average (in best cases the speedup reaches a factor of 18) over the CPU variant while keeping similar tracking accuracy and precision.
Document type :
Conference papers
Complete list of metadata

Cited literature [23 references]  Display  Hide  Download

https://hal.laas.fr/hal-01763095
Contributor : Frédéric Lerasle <>
Submitted on : Tuesday, April 10, 2018 - 5:05:31 PM
Last modification on : Thursday, June 10, 2021 - 3:05:55 AM

File

trade-gpgpu-based.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-01763095, version 1

Citation

Petr Jecmen, Frédéric Lerasle, Alhayat Ali Mekonnen. Trade-off between GPGPU based implementations of multi object tracking particle filter. International Conference on Computer Vision Theory and Applications, Feb 2017, Porto, Portugal. 10p. ⟨hal-01763095⟩

Share

Metrics

Record views

163

Files downloads

293