Accelerated Hypothesis Generation for Multistructure Data via Preference Analysis
Random hypothesis generation is integral to many robust geometric model fitting techniques. Unfortunately, it is also computationally expensive, especially for higher order geometric models and heavily contaminated data. We propose a fundamentally new ...
Active Visual Segmentation
Attention is an integral part of the human visual system and has been widely studied in the visual attention literature. The human eyes fixate at important locations in the scene, and every fixation point lies inside a particular region of arbitrary ...
Divide, Conquer and Coordinate: Globally Coordinated Switching Linear Dynamical System
The goal of this work is to learn a parsimonious and informative representation for high-dimensional time series. Conceptually, this comprises two distinct yet tightly coupled tasks: learning a low-dimensional manifold and modeling the dynamical ...
HMM-Based Lexicon-Driven and Lexicon-Free Word Recognition for Online Handwritten Indic Scripts
Research for recognizing online handwritten words in Indic scripts is at its early stages when compared to Latin and Oriental scripts. In this paper, we address this problem specifically for two major Indic scripts—Devanagari and Tamil. In contrast to ...
Image Restoration by Matching Gradient Distributions
The restoration of a blurry or noisy image is commonly performed with a MAP estimator, which maximizes a posterior probability to reconstruct a clean image from a degraded image. A MAP estimator, when used with a sparse gradient image prior, ...
Mean Shift Trackers with Cross-Bin Metrics
Cross-bin metrics have been shown to be more suitable than bin-by-bin metrics for measuring the distance between histograms in various applications. In particular, a visual tracker that minimizes the earth mover's distance (EMD) between the candidate ...
Metric Rectification of Curved Document Images
In this paper, we propose a metric rectification method to restore an image from a single camera-captured document image. The core idea is to construct an isometric image mesh by exploiting the geometry of page surface and camera. Our method uses a ...
A Multimedia Retrieval Framework Based on Semi-Supervised Ranking and Relevance Feedback
We present a new framework for multimedia content analysis and retrieval which consists of two independent algorithms. First, we propose a new semi-supervised algorithm called ranking with Local Regression and Global Alignment (LRGA) to learn a robust ...
Pedestrian Detection: An Evaluation of the State of the Art
Pedestrian detection is a key problem in computer vision, with several applications that have the potential to positively impact quality of life. In recent years, the number of approaches to detecting pedestrians in monocular images has grown steadily. ...
Quantifying and Transferring Contextual Information in Object Detection
Context is critical for reducing the uncertainty in object detection. However, context modeling is challenging because there are often many different types of contextual information coexisting with different degrees of relevance to the detection of ...
Shared Kernel Information Embedding for Discriminative Inference
Latent variable models, such as the GPLVM and related methods, help mitigate overfitting when learning from small or moderately sized training sets. Nevertheless, existing methods suffer from several problems: 1) complexity, 2) the lack of explicit ...
Task-Driven Dictionary Learning
Modeling data with linear combinations of a few elements from a learned dictionary has been the focus of much recent research in machine learning, neuroscience, and signal processing. For signals such as natural images that admit such sparse ...
M-Idempotent and Self-Dual Morphological Filters
In this paper, we present a comprehensive analysis of self-dual and m--idempotent operators. We refer to an operator as m-idempotent if it converges after m iterations. We focus on an important special case of the general theory of lattice morphology: ...
Model-Based Learning Using a Mixture of Mixtures of Gaussian and Uniform Distributions
We introduce a mixture model whereby each mixture component is itself a mixture of a multivariate Gaussian distribution and a multivariate uniform distribution. Although this model could be used for model-based clustering (model-based unsupervised ...
Two Efficient Solutions for Visual Odometry Using Directional Correspondence
This paper presents two new, efficient solutions to the two-view, relative pose problem from three image point correspondences and one common reference direction. This three-plus-one problem can be used either as a substitute for the classic five-point ...
{\cal U}Boost: Boosting with the Universum
It has been shown that the Universum data, which do not belong to either class of the classification problem of interest, may contain useful prior domain knowledge for training a classifier [1], [2]. In this work, we design a novel boosting algorithm ...