access icon openaccess Rotation angle recovery for rotation invariant detector in lying pose human body detection

A method for rotation-invariant lying-pose human body detection in overlooking images is proposed. The rotation-invariant histogram of oriented gradient using Fourier analysis in polar coordinate is exploited as descriptor for lying-pose human body. And then the authors used the exhaustive sliding window search strategy with multiple scale scan to localise human body. Finally, principal component analysis (PCA) is used to determine the rotation angle of the exhaustive sliding window based on the classifier output scores. Experiments on their built XiaMen University Lying-Pose Dataset (XMULP) show the effectiveness of their proposed method.

Inspec keywords: Fourier analysis; object detection; image classification; principal component analysis

Other keywords: exhaustive sliding window search strategy; Fourier analysis; lying pose human body detection; XMULP dataset; rotation-invariant histogram-of-oriented gradient; classifier output score; overlooking image; rotation invariant detector; principal component analysis; polar coordinate; PCA; rotation angle recovery

Subjects: Other topics in statistics; Optical, image and video signal processing; Mathematical analysis; Mathematical analysis; Computer vision and image processing techniques; Other topics in statistics

References

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