• Publications
  • Influence
As-Projective-As-Possible Image Stitching with Moving DLT
TLDR
We investigate projective estimation under model inadequacies, i.e., when the underpinning assumptions of the projective model are not fully satisfied by the data, thus fundamentally limiting the achievable goodness of fit. Expand
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Fast Supervised Hashing with Decision Trees for High-Dimensional Data
TLDR
We propose to use boosted decision trees for achieving non-linearity in hashing, which are fast to train and evaluate, hence more suitable for hashing with high dimensional data. Expand
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The Random Cluster Model for robust geometric fitting
TLDR
We propose to use Random Cluster Models, a technique used to simulate coupled spin systems, to conduct hypothesis generation using subsets larger than minimal. Expand
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Joint Detection and Estimation of Multiple Objects From Image Observations
TLDR
The problem of jointly detecting multiple objects and estimating their states from image observations is formulated in a Bayesian framework by modeling the collection of states as random finite set. Expand
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A General Two-Step Approach to Learning-Based Hashing
TLDR
We propose a flexible yet simple framework that is able to accommodate different types of loss functions and hash functions. Expand
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Recognizing Human Activities from Silhouettes: Motion Subspace and Factorial Discriminative Graphical Model
  • Liang Wang, D. Suter
  • Mathematics, Computer Science
  • IEEE Conference on Computer Vision and Pattern…
  • 17 June 2007
TLDR
We describe a probabilistic framework for recognizing human activities in monocular video based on simple silhouette observations in this paper. Expand
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As-Projective-As-Possible Image Stitching with Moving DLT
TLDR
We investigate projective estimation under model inadequacies, i.e., when the underpinning assumptions of the projective model are not fully satisfied by the data. Expand
  • 78
  • 19
Dynamic and hierarchical multi-structure geometric model fitting
TLDR
We present a novel dynamic hypothesis generation algorithm for robust fitting of multiple structures based on top-k preference analysis. Expand
  • 101
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A consensus-based method for tracking: Modelling background scenario and foreground appearance
TLDR
We propose an effective and adaptive background modelling method for detecting foreground objects in both static and dynamic scenes. Expand
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Incremental Kernel Principal Component Analysis
TLDR
The kernel principal component analysis (KPCA) has been applied in numerous image-related machine learning applications and it has exhibited superior performance over previous approaches, such as PCA. Expand
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