Hybrid tracking and visual search

ABSTRACT

Robust local features such as SIFT and SURF have been applied to many interesting image matching applications. These features are by nature very computational intensive even for modern desktop PCs. We have developed a framework for efficient feature extraction and matching for still images on a mobile device. In this paper we extend the still-image framework to video sequences. It is inefficient to perform feature extraction and matching for each frame in the video sequence. By tracking the content of the frames, feature extraction and image matching need only be performed when there is new content. We show promising experimental results using this approach.

REFERENCES

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.4 IMAGE PROCESSING AND COMPUTER VISION
      I.4.9 Applications

Additional Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval

General Terms:
Algorithms, Design, Experimentation, Performance

Keywords:
image matching, robust local feature, tracking