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Finding Text in Natural Scenes by Figure-Ground Segmentation

Finding Text in Natural Scenes by Figure-Ground Segmentation

引用

International conference on pattern recognition

作者： Huiying Shen J. Coughlan Smith-Kettlewell Eye Research Institute San Francisco CA USA

Much past research on finding text in natural scenes uses bottom-up grouping processes to detect candidate text features as a first processing step. While such grouping procedures are a fast and efficient way of extracting the parts of an image that are most likely to contain text, they still suffer from large amounts of false positives that must be pruned out before they can be read by OCR. We argue that a natural framework for pruning out false positive text features is figure-ground segmentation. This process is implemented using a graphical model (i.e. MRF) in which each candidate text feature is represented by a node. Since each node has only two possible states (figure and ground), and since the connectivity of the graphical model is sparse, we can perform rapid inference on the graph using belief propagation. We show promising results on a variety of urban and indoor scene images containing signs, demonstrating the feasibility of the approach

关键词： Layout Graphical models Image segmentation computer vision Optical character recognition software Context modeling Image resolution Belief propagation Optical filters Character recognition

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3D Modelling from Multi-view Registered Range Images Using K-means Clustering

3D Modelling from Multi-view Registered Range Images Using K...

引用

IEEE International conference on Industrial Technology (ICIT)

作者： Hong Zhou Yonghuai Liu Department of Computer Science University of Wales Ceredigion UK

3D modelling from range images captured using laser scanning systems finds a wide range of applications in computer vision and industrial robotics. However due to the presence of scanning noise, accumulative registration errors, and improper data fusion, the reconstructed surfaces from multiple registered range images captured from different viewpoints are often distorted with thick patches, false connections and blurred features. Moreover, the existing integration methods are often expensive in the sense of computational time and data storage. These shortcomings will hinder the wide applications of 3D modelling using the latest laser scanning systems. In this paper, the k-means clustering approach from the pattern recognition and machine learning literatures is employed to optimally fuse the overlapping areas between two range images captured from two neighbouring viewpoints and to iteratively minimize the integration error. The final fused point set is then triangulated using an improved Delaunay method, guaranteeing a watertight surface. The new method is theoretically guaranteed to converge. A comparative study based on real images shows that the proposed algorithm is computationally efficient and significantly reduces the integration error, while desirably retaining geometric details of object surface.

关键词： Laser modes Laser noise Laser fusion Application software computer vision computer industry Service robots Robot sensing systems Robot vision systems computer errors

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A Neuropsychology-inspired Learning System for Human Uncertainty Monitoring

A Neuropsychology-inspired Learning System for Human Uncerta...

引用

International conference on Control, Automation, Robotics and vision (ICARCV)

作者： T. Z. Tan G. S. Ng S. S. Erdogan SCHOOL OF COMPUTER Engineering Nanyang Technological University Singapore DEPARTMENT OF COMPUTER SCIENCE University of Hawai Hilo USA

Uncertainty exists in various complex problems. Yet, human is able to effectively handle these uncertainties and makes appropriate decision. Thus, modeling of human uncertainty process should improve the performance of learning system in uncertain environment. A mechanism for human uncertainty monitoring is the broad and narrow generalization in category learning. This can be modeled using upper and lower membership functions, which corresponds to the broad and narrow generalizations respectively. These upper and lower membership functions can be implemented using the fuzzy rough set (FR) theory. A complementary learning fuzzy neural network (CLFNN) is a functional model of human pattern recognition. It is integrated with the human uncertainty monitoring model and the resultant FRCLFNN offers good classification performance and better representation power as it captures input, linguistic, and rough uncertainties. Experimental result supports that FRCLFNN is a competent decision support system

关键词： Learning systems Humans Uncertainty Decision support systems Fuzzy neural networks Decision making Artificial neural networks computerized monitoring Fuzzy set theory Power system modeling

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Hand Posture Classification and recognition using the Modified Census Transform

Hand Posture Classification and Recognition using the Modifi...

引用

International conference on Automatic Face and Gesture recognition

作者： A. Just Y. Rodriguez S. Marcel Ecole Polytechnique Fédérale de Lausanne EPFL IDIAP Research Institute Martigny Switzerland

Developing new techniques for human-computer interaction is very challenging. vision-based techniques have the advantage of being unobtrusive and hands are a natural device that can be used for more intuitive interfaces. But in order to use hands for interaction, it is necessary to be able to recognize them in images. In this paper, we propose to apply to the hand posture classification and recognition tasks an approach that has been successfully used for face detection (B. Froba and A. Ernst, 2004). The features are based on the modified census transform and are illumination invariant. For the classification and recognition processes, a simple linear classifier is trained, using a set of feature lookup-tables. The database used for the experiments is a benchmark database in the field of posture recognition. Two protocols have been defined. We provide results following these two protocols for both the classification and recognition tasks. Results are very encouraging

关键词： Face recognition pattern recognition Human computer interaction Spatial databases Protocols Image databases Face detection Feature extraction Image recognition Lighting

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Multiple Objects Tracking with Multiple Hypotheses Graph Representation

Multiple Objects Tracking with Multiple Hypotheses Graph Rep...

引用

International conference on pattern recognition

作者： Alex Yong Sang Chia Weimin Huang Liyuan Li Institute for Infocomm Research Singapore

ISBN: (纸本)0769525210

We present a novel multi-object tracking algorithm based on multiple hypotheses about the trajectories of the objects. Our work is inspired by Reid's multiple hypothesis tracking algorithm which is an optimal solution to the motion correspondence that occurs in multi-object tracking. Unfortunately, the exponential growth of the hypotheses tree precludes practical applications. To restrict this growth, many approximations relying on a series of clustering and pruning operations have been proposed. The decisions for these operations are based solely on previous observations and are not guided by observations in later frames. We show that due to multiple splits and merges, relying solely on previous observations to guide these operations may inadvertently eliminate the correct hypothesis. Consequently, this leads to poor tracking performance. To overcome this problem, we determine the validity of a hypothesis by exploiting information in later frames and relating them to previous observations. Experimental results demonstrate the robustness and efficiency of our approach

关键词： Robustness Trajectory Video sequences Tracking Clustering algorithms computer vision Lead Upper bound Layout Cameras

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Detection Over Viewpoint via the Object Class Invariant

Detection Over Viewpoint via the Object Class Invariant

引用

International conference on pattern recognition

作者： M. Toews T. Arbel Centre for Intelligent Machines McGill University Montreal Canada

ISBN: (纸本)0769525210

In this article, we present a new model of object class appearance over viewpoint, based on learning a relationship between scale-invariant image features (e.g. SIFT) and a geometric structure that we refer to as an OCI (object class invariant). The OCI is a perspective invariant defined across instances of an object class, and thereby serves as a common reference frame relating features over viewpoint change and object class. A single probabilistic OCI model can be learned to capture the rich multimodal nature of object class appearance in the presence of viewpoint change, providing an efficient alternative to the popular approach of training a battery of detectors at separate viewpoints and/or poses. Experimentation demonstrates that an OCI model of faces can be learned from a small number of natural, cluttered images, and used to detect faces exhibiting a large degree of appearance variation due to viewpoint change and intra-class variability (i.e. (sun)glasses, ethnicity, expression, etc.)

关键词： Object detection Face detection Detectors Batteries computer vision Machine learning Robustness Lighting Image databases Spatial databases

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Classifiers for Motion

Classifiers for Motion

引用

International conference on pattern recognition

作者： M.D. Gupta S. Rajaram N. Petrovic T.S. Huang University of Illinois Urbana IL USA Google Inc. New York NY USA

ISBN: (纸本)0769525210

In this paper, we present a supervised learning based approach for sub-pixel motion estimation. The novelty of this work is the learning based method itself which tries to learn the shifts from a large training database. Integer pixel shift is sub-divided and discretized to levels in both the horizontal and vertical direction. We pose the problem of motion estimation in a polar coordinate system. Shift estimation in the x and y direction has been posed as a problem of estimating r and thetas. The ordinal property of r has been used, and consequently, we employ a ranking based approach for estimating r. For thetas estimation we employ multi-class classification techniques. We demonstrate how very simplistic features can be used to differentiate between different sub-pixel shifts

关键词： Motion estimation Supervised learning computer vision Cities and towns Learning systems Databases Spatial resolution Application software Biomedical optical imaging Optical sensors

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Note on Feature Selection for Polyp Detection in CT Colonography

Note on Feature Selection for Polyp Detection in CT Colonogr...

引用

International conference on pattern recognition

作者： T.A. Chowdhury O. Ghita P.F. Whelan A. Miranda Vision Systems Group School of Electronic Engineering University of Dublin Dublin Ireland

In this paper we describe a computer aided detection (CAD) algorithm for robust detection of polyps in computed tomography (CT) colonography. The devised algorithm identifies suspicious polyp candidate surfaces using the surface normal intersection, Hough transform, 3D histogram analysis, region growing and a convexity test. From these detected surfaces we extract statistical and morphological features in order to evaluate if the surface in question is a polyp or fold. In order to devise the optimal classification scheme the performance of two different classifiers are evaluated when the algorithm is applied to synthetic and real patient data. The experimental results indicate that the overall polyp detection performance shows sensitivity higher than 92% for polyps larger than 5mm with an average of 4.7 to 6.0 false positives per dataset

关键词： Colonic polyps Virtual colonoscopy Surface morphology Computed tomography Robustness Colonography Histograms Algorithm design and analysis Testing Data mining

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A novel technique for the watermarking of symbolically compressed documents

A novel technique for the watermarking of symbolically compr...

引用

International Workshop on Document Image Analysis for Libraries

作者： S. Palit U. Garain Computer Vision and Pattern Recognition Unit

Symbolic compression is a lossy compression technique which has been found to perform very efficiently for Indian language text document images. A novel and efficient watermarking technique is proposed for such documents compressed symbolically. The approach embeds the watermark into prototypes which are unaffected during compression, leading to an exact recovery of the watermark both from the compressed document and the reconstructed one. The watermark is perfectly resistant to JPEG conversion and reasonably resistant to other attacks. The proposed technique, for the first time, combines the compression and watermarking of Indian language text document images in a common framework

关键词： Watermarking Image coding Data encapsulation Image storage Image reconstruction Prototypes Immune system Software libraries Communication standards computer vision

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Object localization/segmentation using generic shape priors

Object localization/segmentation using generic shape priors

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International conference on pattern recognition

作者： M. Fussenegger A. Opelt A. Pinz Institute of Electrical Measurement and Measurement Signal Processing Graz University of Technology Austria

Generally object segmentation is an ill-posed problem. Approaches that use only plain image information will often fail. To overcome these limitations, prior knowledge (like information of the object contour) can be added to the segmentation process. In this paper, we present a novel generic shape model. We use the expertise from the field of object class recognition, namely a boundary-fragment-model (BFM) as prior knowledge for our level set segmentation approach. Commonly, shape models need synthetically generated or pre-segmented training sets that are usually trained on one specific object or a small group of objects. With our new approach we are able to train shape models for whole categories, which makes the segmentation method much more flexible. Additionally we overcome the difficulty of the correct initialization and reduce the segmentation effort. Experimental results demonstrate the excellent performance of our method on different types of objects (categories)

关键词： Image segmentation Electric variables measurement Level set Training data Signal processing Object segmentation computer vision Probability density function Active shape model Solid modeling

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