In visual recognition tasks, the design of low level im- age feature representation is fundamental. The advent of local patch features from pixel attributes ...
scholar.google.com › citations
In this paper, we present a supervised framework to embed the image level label information into the design of patch level kernel descriptors, which we call ...
A family of kernel descriptors which provide a unified and principled framework to turn pixel attributes (gradient, color, local binary pattern, \etc) into ...
Missing: Supervised | Show results with:Supervised
This work highlights the kernel view of orientation histograms, and shows that they are equivalent to a certain type of match kernels over image patches, ...
In this paper, we present a supervised framework to embed the image level label information into the design of patch level kernel descriptors, which we call ...
In particular, we introduce three types of match kernels to measure similarities between image patches, and construct compact low-dimensional kernel descriptors ...
It has been shown that the Histogram Intersection Kernel (HIK) is more effective than the Euclidean distance in supervised learning tasks with histogram ...
In this paper, we present a supervised framework to embed the image level label information into the design of patch level kernel descriptors, which we call ...
Our low-level image feature extractors, kernel descrip- tors, consist of three steps: (1) design match kernels using pixel attributes; (2) learn compact basis.
Missing: Supervised | Show results with:Supervised
Apr 10, 2015 · In this paper, we present a supervised framework to embed the image level label information into the design of patch level kernel descriptors, ...