Guest Editorial: Similarity Matching in Computer Vision and Multimedia
Computer Vision and Image Understanding
Viewpoint Invariant Pedestrian Recognition with an Ensemble of Localized Features
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Scaling Up a Metric Learning Algorithm for Image Recognition and Representation
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing, Part II
Weighted locally linear embedding for dimension reduction
Pattern Recognition
Proceedings of the 18th international conference on World wide web
A Random Extension for Discriminative Dimensionality Reduction and Metric Learning
IbPRIA '09 Proceedings of the 4th Iberian Conference on Pattern Recognition and Image Analysis
Beyond distance measurement: constructing neighborhood similarity for video annotation
IEEE Transactions on Multimedia - Special section on communities and media computing
Supervised learning of similarity measures for content-based 3D model retrieval
LKR'08 Proceedings of the 3rd international conference on Large-scale knowledge resources: construction and application
The quadratic-chi histogram distance family
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part II
Collection-based sparse label propagation and its application on social group suggestion from photos
ACM Transactions on Intelligent Systems and Technology (TIST)
Shape analysis for power signal cryptanalysis on secure components
Journal of Systems and Software
Pedestrian recognition with a learned metric
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part IV
Dynamic time warping constraint learning for large margin nearest neighbor classification
Information Sciences: an International Journal
Fast shape re-ranking with neighborhood induced similarity measure
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part I
Object flow: learning object displacement
ACCV'10 Proceedings of the 2010 international conference on Computer vision - Volume Part I
Positive semidefinite metric learning using boosting-like algorithms
The Journal of Machine Learning Research
Cartoon features selection using Diffusion Score
Signal Processing
Intelligent Data Analysis - Combined Learning Methods and Mining Complex Data
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In this paper, we present a general guideline to find a better distance measure for similarity estimation based on statistical analysis of distribution models and distance functions. A new set of distance measures are derived from the harmonic distance, the geometric distance, and their generalized variants according to the Maximum Likelihood theory. These measures can provide a more accurate feature model than the classical Euclidean and Manhattan distances. We also find that the feature elements are often from heterogeneous sources that may have different influence on similarity estimation. Therefore, the assumption of single isotropic distribution model is often inappropriate. To alleviate this problem, we use a boosted distance measure framework that finds multiple distance measures which fit the distribution of selected feature elements best for accurate similarity estimation. The new distance measures for similarity estimation are tested on two applications: stereo matching and motion tracking in video sequences. The performance of boosted distance measure is further evaluated on several benchmark data sets from the UCI repository and two image retrieval applications. In all the experiments, robust results are obtained based on the proposed methods.