Imperial College London


Faculty of EngineeringDepartment of Electrical and Electronic Engineering

Reader in Computer Vision



+44 (0)20 7594 6220k.mikolajczyk




Electrical EngineeringSouth Kensington Campus






BibTex format

author = {Chan, CH and Yan, F and Kittler, J and Mikolajczyk, K},
doi = {10.1016/j.patcog.2014.10.010},
journal = {Pattern Recognition},
pages = {1324--1332},
title = {Full ranking as local descriptor for visual recognition: A comparison of distance metrics on sn},
url = {},
volume = {48},
year = {2015}

RIS format (EndNote, RefMan)

AB - © 2014 Elsevier Ltd. All rights reserved. In this paper we propose to use the full ranking of a set of pixels as a local descriptor. In contrast to existing methods which use only partial ranking information, the full ranking encodes the complete comparative information among the pixels, while retaining invariance to monotonic photometric transformations. The descriptor is used within the bag-of-visual-words paradigm for visual recognition. We demonstrate that the choice of distance metric for assigning the descriptors to visual words is crucial to the performance, and provide an extensive evaluation of eight distance metrics for the permutation group Sn on four widely used face verification and texture classification benchmarks. The results demonstrate that (1) full ranking of pixels encodes more information than partial ranking, consistently leading to better performance; (2) full ranking descriptor can be trivially made rotation invariant; (3) the proposed descriptor applies to both image intensities and filter responses, and is capable of producing state-of-the-art performance.
AU - Chan,CH
AU - Yan,F
AU - Kittler,J
AU - Mikolajczyk,K
DO - 10.1016/j.patcog.2014.10.010
EP - 1332
PY - 2015///
SN - 0031-3203
SP - 1324
TI - Full ranking as local descriptor for visual recognition: A comparison of distance metrics on sn
T2 - Pattern Recognition
UR -
VL - 48
ER -