Robust Radiometric Calibration and Vignetting Correction
In many computer vision systems, it is assumed that the image brightness of a point directly reflects the scene radiance of the point. However, the assumption does not hold inmost cases due to nonlinear camera response function, exposure changes, and ...
Border and Surface Tracing - Theoretical Foundations
In this paper we define and study digital manifolds of arbitrary dimension, and provide (in particular)a general theoretical basis for curve or surface tracing in picture analysis. The studies involve properties such as one-dimensionality of digital ...
Geometric Rectification of Camera-Captured Document Images
Compared to typical scanners, handheld cameras offer convenient, flexible, portable, and non-contact image capture, which enables many new applications and breathes new life into existing ones. However,camera-captured documents may suffer from ...
Maximum Confidence Hidden Markov Modeling for Face Recognition
This paper presents a hybrid framework of feature extraction and hidden Markov modeling(HMM) for two-dimensional pattern recognition. Importantly, we explore a new discriminative training criterion to assure model compactness and discriminability. This ...
Image Stitching Using Structure Deformation
The aim of this paper is to achieve seamless image stitching without producing visual artifact caused by severe intensity discrepancy and structure misalignment, given that the input images are roughly aligned or globally registered. Our new approach is ...
MAC: Magnetostatic Active Contour Model
We propose an active contour model using an external force field that is based on magnetostatics and hypothesized magnetic interactions between the active contour and object boundaries. The major contribution of the method is that the interaction of its ...
Bayes Optimality in Linear Discriminant Analysis
We present an algorithm which provides the one-dimensional subspace where the Bayes error is minimized for the C class problem with homoscedastic Gaussian distributions. Our main result shows that the set of possible one-dimensional spaces v, for which ...
Between Classification-Error Approximation and Weighted Least-Squares Learning
This paper presents a deterministic solution to an approximated classification-error based objective function. In the formulation, we propose a quadratic approximation as the function for achieving smooth error counting. The solution is subsequently ...
Dependent Multiple Cue Integration for Robust Tracking
We propose a new technique for fusing multiple cues to robustly segment an object from its background in video sequences that suffer from abrupt changes of both illumination and position of the target. Robustness is achieved by the integration of ...
Hole Filling of a 3D Model by Flipping Signs of a Signed Distance Field in Adaptive Resolution
When we use range finders to observe the shape of an object, many occluded areas may occur. These become holes and gaps in the model and make it undesirable for various applications. We propose a novel method to fill holes and gaps to complete this ...
Unsupervised Learning of Discriminative Edge Measures for Vehicle Matching between Nonoverlapping Cameras
This paper proposes a novel unsupervised algorithm learning discriminative features in the context of matching road vehicles between two non-overlapping cameras. The matching problem is formulated as a same-different classification problem, which aims ...
Scene Classification Using a Hybrid Generative/Discriminative Approach
We investigate whether dimensionality reduction using a latent generative model is beneficial for the task of weakly supervised scene classification. In detail we are given a set of labelled images of scenes (e.g. coast, forest, city, river, etc) and ...
An Improved Physically-Based Method for Geometric Restoration of Distorted Document Images
In document digitization through camera-based systems, simple imaging setups often produce geometric distortions in the resultant 2D images because of the non-planar geometric shapes of certain documents such as thick bound books, rolled, folded or ...
Error-Dependency Relationships for the Naïve Bayes Classifier with Binary Features
We derive a tight dependency-related bound on the difference between the Naïve Bayes (NB) error and Bayes error for two binary features and two equiprobable classes. A measure of discrepancy of feature dependencies is proposed for multiple features. Its ...
A Rich Discrete Labeling Scheme for Line Drawings of Curved Objects
We present a discrete labeling scheme for line drawings of curved objects which can be seen as an information-rich extension of the classic line-labeling scheme in which lines are classified as convex, concave, occluding or extremal. New labels are ...
Robust Foreground Detection In Video Using Pixel Layers
A framework for robust foreground detection that works under difficult conditions such as dynamic background and moderately moving camera is presented in this paper. The proposed method includes two main components: coarse scene representation as the ...
