Authors:
Juan Carlos León
;
Fabio Martínez
and
Eduardo Romero
Affiliation:
Universidad Nacional de Colombia, Colombia
Keyword(s):
Background Subtraction, Motion Analysis, SD Estimation.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Image and Video Analysis
;
Segmentation and Grouping
Abstract:
This paper introduces a novel method for segmenting the human silhouette in video sequences, based on a local version of the classical SD filter. A main difference of our approach is that the filter is not pixelwise oriented, but rather region wise adjusted by using scaled estimations of both the pixel intensity and the horizontal (vertical) gradient, i.e., a multiresolution wavelet decomposition using Haar functions. The classical SD filter is independently applied to each component of the obtained feature vector, previously normalized and
a single scalar value is associated to the pixel by averaging the feature vector components. The background is estimated by setting a threshold in a histogram constructed with these integrated values, attempting to maximize the interclass variance. This strategy was evaluated in a set of 6 videos, taken from the Human Eva data set. Results show that the proposed algorithm provides a better segmentation of the human silhouette, specially in the lim
bs, which are critical for human movement analysis.
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