'''LESH (Local Energy energy-based Shapeshape Histogramhistogram (LESH)''' is a robustproposed [[image descriptor that can be used]] in [[computer vision tasks]]. It can be used to get an efficienta 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 well, 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-dimentionaldimensional 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 etc]].
== See also ==
* [[Feature detection (computer vision)]]
* [[Scale-invariant feature transform]]
* [[SURF | Speeded Up Robustup Featuresrobust features]]
*[http://www.cv.tu-berlin.de/publicationsfileadmin/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).]
