Soft-assigned bag of features tracking

Zhongyan Qiu, Tong Yu, Tongwei Ren, Yan Liu, Jia Bei

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)


Bag of features (BoF) provides an effective and efficient representation for object tracking in video sequences. However, hard assignment used in BoF generation inevitably brings in quantization errors, which may lead to inaccuracy even failure in tracking. In this paper, we propose a novel soft-assigned bag of features tracking approach (SABoF), which can significantly reduce the influence of quantization errors and obtain more accurate and stable tracking results. We initialize tracking by specifying the tracked object and constructing the codebook. Then, we represent each candidate target with soft-assigned BoF and measure its similarity to the tracked object. The most similar candidate target in each frame is selected as the tracked result. To improve tracking performance, we also refine the tracking results by combining incremental PCA tracking. The proposed approach is evaluated on the challenging video sequences from CAVIAR dataset. Experiments show our approach outperforms current dominant methods in complex conditions.
Original languageEnglish
Title of host publicationICIMCS 2013 - Proceedings of the 5th International Conference on Internet Multimedia Computing and Service
Number of pages4
Publication statusPublished - 16 Sept 2013
Event5th International Conference on Internet Multimedia Computing and Service, ICIMCS 2013 - Huangshan, China
Duration: 17 Aug 201319 Aug 2013


Conference5th International Conference on Internet Multimedia Computing and Service, ICIMCS 2013


  • bag of features
  • object tracking
  • soft assignment

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software


Dive into the research topics of 'Soft-assigned bag of features tracking'. Together they form a unique fingerprint.

Cite this