Local energy-based shape histogram: Difference between revisions

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'''LESH (Local Energy energy-based Shapeshape Histogramhistogram (LESH)''' is a recently proposed [[image descriptor]] in [[computer vision]]. It can be used to get a description of the underlying shape. The LESH feature descriptor is built on local energy model of feature perception, see e.g. [[phase congruency]] for more details. It encodes the underlying shape by accumulating local energy of the underlying signal along several filter orientations, several local [[histograms]] from different parts of the image/patch are generated and concatenated together into a 128-dimensional compact spatial histogram. It is designed to be [[scale invariant]]. The LESH features can be used in applications like shape-based image retrieval, medical image processing, object detection, and [[3D Pose Estimation|pose estimation]].

== See also ==

* [[Feature detection (computer vision)]]

* [[Scale-invariant feature transform]]

* [[SURF|Speeded Upup Robustrobust Featuresfeatures]]

* [[GLOH|Gradient Location Orientation Histogram]]

== References ==

* Code: {{GitHub|ssarfraz/LESH}}

*[http://www.cv.tu-berlin.de/fileadmin/fg140/Head_Pose_Estimation.pdf Sarfraz, S., Hellwich, O.:"Head Pose Estimation in Face Recognition across Pose Scenarios", Proceedings of VISAPP 2008, Int. conference on Computer Vision Theory and Applications, Madeira, Portugal, pp. 235-242, January 2008 (Best Student Paper Award).]