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Object tracking using AM-FM image features

Object tracking using AM-FM image features

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© The Institution of Engineering and Technology
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AM-FM models analyse an image in terms of amplitude (AM) and frequency modulated (FM) sinusoids. In this study, the authors present detection and tracking of single and multiple objects in video sequences using AM-FM features. The authors use the particle filtering framework for estimating the motion parameters. The single object tracking algorithm uses an affine motion model and a subspace-based appearance model. The multiple object tracking algorithm, which is a logical extension of single object tracking, can handle varying number of interacting objects. The performance of both single and multiple object tracking is illustrated on real-world videos.

Inspec keywords: motion estimation; image sequences; object detection; target tracking; amplitude modulation; frequency modulation

Other keywords: objects detection; motion estimation; AM-FM image features; frequency modulated sinusoid; amplitude modulated sinusoid; object tracking; subspace-based appearance model; affine motion model; particle filtering; video sequences

Subjects: Computer vision and image processing techniques; Video signal processing; Modulation and coding methods; Optical, image and video signal processing

References

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