Multi-peak estimation for real-time 3D ping-pong ball tracking with double-queue based GPU acceleration

Ziwei Deng, Yilin Hou, Xina Cheng, Takeshi Ikenaga

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

3D ball tracking is of great significance in ping-pong game analysis, which can be utilized to applications such as TV contents and tactic analysis, with some of them requiring real-time implementation. This paper proposes a CPU-GPU platform based Particle Filter for multiview ball tracking including 4 proposals. The multi-peak estimation and the ball-like observation model are proposed in the algorithm design. The multi-peak estimation aims at obtaining a precise ball position in case the particles' likelihood distribution has multiple peaks under complex circumstances. The ball-like observation model with 4 different likelihood evaluation, utilizes the ball's unique features to evaluate the particle's similarity with the target. In the GPU implementation, the double-queue structure and the vectorized data combination are proposed. The double-queue structure aims at achieving task parallelism between some data-independent tasks. The vectorized data combination reduces the time cost in memory access by combining 3 different image data to 1 vector data. Experiments are based on ping-pong videos recorded in an official match taken by 4 cameras located in 4 corners of the court. The tracking success rate reaches 99.59% on CPU. With the GPU acceleration, the time consumption is 8.8 ms/frame, which is sped up by a factor of 98 compared with its CPU version.

Original languageEnglish
Pages (from-to)1251-1259
Number of pages9
JournalIEICE Transactions on Information and Systems
VolumeE101D
Issue number5
DOIs
Publication statusPublished - 2018 May 1

Keywords

  • 3D ball tracking
  • GPU acceleration
  • Heterogeneous computing
  • OpenCL
  • Particle filter
  • Sports analysis

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Artificial Intelligence

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