Abstract - A fl exible multiscale and directional representation for images is proposed. The scheme combines directional fi lter banks with the Laplacian pyramid to provides a sparse representation for two- dimensional piecewise smooth signals resembling images. The underlying expansion is a frame and can be designed to be a tight frame. pyramidal directional fi lter banks provide an effective method to implement the digital curvelet transform. The regularity issue of the iterated fi lters in the directional fi lter bank is examined.
标签： representation directional multiscale Abstract
上传时间： 2013-12-15
上传用户：zxc23456789
The object detector described below has been initially proposed by P.F. Felzenszwalb in [Felzenszwalb2010]. It is based on a Dalal-Triggs detector that uses a single filter on histogram of oriented gradients (HOG) features to represent an object category. This detector uses a sliding window approach, where a filter is applied at all positions and scales of an image. The first innovation is enriching the Dalal-Triggs model using a star-structured part-based model defined by a “root” filter (analogous to the Dalal-Triggs filter) plus a set of parts filters and associated deformation models. The score of one of star models at a particular position and scale within an image is the score of the root filter at the given location plus the sum over parts of the maximum, over placements of that part, of the part filter score on its location minus a deformation cost easuring the deviation of the part from its ideal location relative to the root. Both root and part filter scores are defined by the dot product between a filter (a set of weights) and a subwindow of a feature pyramid computed from the input image. Another improvement is a representation of the class of models by a mixture of star models. The score of a mixture model at a particular position and scale is the maximum over components, of the score of that component model at the given location.
标签： 计算机视觉
上传时间： 2015-03-15
上传用户：sb_zhang
