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ICPR
2004
IEEE

Action and Simultaneous Multiple-Person Identification Using Cubic Higher-Order Local Auto-Correlation

9 years 6 months ago
Action and Simultaneous Multiple-Person Identification Using Cubic Higher-Order Local Auto-Correlation
We propose a new method ? Cubic Higher-order Local Auto-Correlation (CHLAC) ? to address three-way data analysis. This method is a natural extension of Higherorder Local Auto-Correlation (HLAC) [6], which deals only with two-way data. Both methods use "correlation" to summarize relative positions or motions within a local data region, and these can be calculated simply with a low computational load. Moreover, our new method (CHLAC) offers several preferable properties as well as HLAC: shiftinvariance to data (rendering the method segmentationfree), additivity for data, and robustness to noise in data. In this study, we applied this method to action and simultaneous multiple-person identification from a motion-image sequence through the property of data additivity. Experimental results showed that this method performed well.
Nobuyuki Otsu, Takumi Kobayashi
Added 09 Nov 2009
Updated 09 Nov 2009
Type Conference
Year 2004
Where ICPR
Authors Nobuyuki Otsu, Takumi Kobayashi
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