Paper
2 October 1998 Multilevel dynamic attention map for human face detection
Masaru Tanaka, Kazuhiro Hotta, Takio Kurita, Taketoshi Mishima
Author Affiliations +
Abstract
The face recognition, as one of the pattern recognition, includes various essence such as the representation and the extraction of the required features, the classification based on the obtained features and the detecting specified regions etc. Previously, we presented the scale and the rotation invariant face recognition method based on both Higher-Order Local Autocorrelation features of log-polar image and linear discriminant analysis for 'face' and 'not face' classification. In this face recognition method, the searching for the 'face' region was performed randomly or sequentially on the image. Therefore its searching performance was not satisfiable. In this paper, we present a method to narrow down the search space by dynamically using the information obtained at the previous search point through constructing the multilevel dynamic attention map, which is constructed based on the Ising dynamics and the renormalization group method.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Masaru Tanaka, Kazuhiro Hotta, Takio Kurita, and Taketoshi Mishima "Multilevel dynamic attention map for human face detection", Proc. SPIE 3454, Vision Geometry VII, (2 October 1998); https://doi.org/10.1117/12.323263
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Facial recognition systems

Image classification

Distance measurement

Feature extraction

Magnetism

Pattern recognition

RGB color model

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