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Watershed segmentation based on inertial product energy

Watershed segmentation based on inertial product energy

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Chinese conference on pattern recognition

作者： Ma, Jinwei Xue, Heru Su, Changming College of Computer and Information Engineering of Inner Mongolia Agricultural University Huhehaote 010018 China College of Information Science and Technology of Chengdu University Chengdu 610106 China

ISBN: (纸本)9781424472109

An image segmentation method is presented based on the inertial product energy to construct a good watershed structure for gradient level image and improve watershed segmentation. The inertial product energy can weaken the noises and tiny edges in gradient level image. Then a non-linear processing.classification and filtering based on fusion and adaptive are employed to reduce the influence of a lot of local minimum pixels which are less sensible in the inertial product energy image. Thus the inertial product energy image has a good watershed structure. Experimental results show that the proposed method significantly decrease the over-segmentation and provides a reliable basis for further processing. ©2010 ieee.

关键词： image segmentation

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Dealing with occlusions in the eigenspace approach

Dealing with occlusions in the eigenspace approach

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conference on computer Vision and pattern recognition (CVPR)

作者： A. Leonardis H. Bischof Department for Pattern Recognition and Image Processing Technical University of of Vienna Vienna Austria

The basic limitations of the current appearance-based matching methods using eigenimages are non-robust estimation of coefficients and inability to cope with problems related to occlusions and segmentation. In this paper we present a new approach which successfully solves these problems. The major novelty of our approach lies in the way how the coefficients of the eigenimages are determined. Instead of computing the coefficients by a projection of the data onto the eigenimages, we extract them by a hypothesize-and-test paradigm using subsets of image points. Competing hypotheses are then subject to a selection procedure based on the Minimum Description Length principle. The approach enables us not only to reject outliers and to deal with occlusions but also to simultaneously use multiple classes of eigenimages.

关键词： Lighting Robustness Data mining Shape computer vision Electric breakdown pattern recognition image processing pattern matching image segmentation

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Vector-valued image regularization with PDE's: a common framework for different applications

Vector-valued image regularization with PDE's: a common fram...

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conference on computer Vision and pattern recognition (CVPR)

作者： D. Tschumperle R. Deriche Odyssée Laboratory INRIA Sophia-Antipolis France

We address the problem of vector-valued image regularization with variational methods and PDEs. From the study of existing formalisms, we propose a unifying framework based on a very local interpretation of the regularization processes. The resulting equations are then specialized into new regularization PDEs and corresponding numerical schemes that respect the local geometry of vector-valued images. They are finally applied on a wide variety of image processing.problems, including color image restoration, in-painting, magnification and flow visualization.

关键词： Equations Geometry Smoothing methods image processing image restoration Anisotropic magnetoresistance Symmetric matrices Tensile stress Chemical elements Color

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Connectionist networks for feature indexing and object recognition

Connectionist networks for feature indexing and object recog...

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conference on computer Vision and pattern recognition (CVPR)

作者： C.F. Olson Department of Computer Science Cornell University Ithaca NY USA

Feature indexing techniques are promising for object recognition since they can quickly reduce the set of possible matches for a set of image features. This work exploits another property of such techniques. They have inherently parallel structure and connectionist network formulations are easy to develop. Once indexing has been performed, a voting scheme such as geometric hashing can be used to generate object hypotheses in parallel. We describe a framework for the connectionist implementation of such indexing and recognition techniques. With sufficient processing.elements, recognition can be performed in a small number of time steps. The number of processing.elements necessary to achieve peak performance and the fan-in/fan-out required for the processing.elements is examined. These techniques have been simulated on a conventional architecture with good results.

关键词： Indexing Object recognition image recognition computer science Voting Parallel processing Bayesian methods computer vision Feature extraction Broadcasting

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On texture in document images

On texture in document images

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conference on computer Vision and pattern recognition (CVPR)

作者： A.K. Jain S.K. Bhattacharjee Y. Chen Pat tern Recognition & Image Processing Laboratory Computer Science Department Michigan State University East Lansing MI USA Dept. of Comput. Sci. Michigan State Univ. East Lansing MI USA

A multichannel filtering-based texture segmentation method is applied to a variety of document image processing.problems: text-graphics separation, address-block location, and bar code localization. In each of these segmentation problems, the text context or bar code in the image is considered to define a unique texture. Thus, all three document analysis problems can be posed as texture segmentation problems. Two-dimensional Gabor filters are used to compute texture features. Both supervised and unsupervised methods are used to identify regions of text or bar code in the document images. The performance of the segmentation and classification scheme for a variety of document images demonstrates the generality and effectiveness of the approach.< >

关键词： Gabor filters image segmentation Pixel Frequency image recognition image processing Laboratories computer science Application software Document image processing

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Registration of camera captured documents under non-rigid deformation

Registration of camera captured documents under non-rigid de...

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作者： Edupuganti, Venkata Gopal Agarwal, Vinayak A Kompalli, Suryaprakash Dept. of Computer Science New Jersey Inst. of Technology Newark NJ United States Stanford University Stanford CA United States Hewlett-Packard Labs Bangalore India

ISBN: (纸本)9781457703942

Document registration is a problem where the image of a template document whose layout is known is registered with a test document image. Given the registration parameters, layout of the template image is superimposed on the test document. Registration algorithms have been popular in applications, such as forms processing.where the superimposed layout is used to extract relevant fields. Prior art has been designed to work with scanned documents under affine transformation. We find that the proliferation of camera captured images makes it necessary to address camera noise such as non-uniform lighting, clutter, and highly variable scale/resolution. The absence of a scan bed also leads to challenging non-rigid deformations being seen in paper images. Prior approaches in point pattern based registration like RANdom SAmple Consensus (RANSAC) [4], and Thin Plate Spline-Robust Point Matching (TPS-RPM) [5, 6] form the basis of our work. We propose enhancements to these methods to enable registration of cell phone and camera captured documents under non-rigid transformations. We embed three novel aspects into the framework: (i) histogram based uniformly transformed correspondence estimation, (ii) clustering of points located near the regions of interest (ROI) to select only close by regions for matching, (iii) validation of the registration in RANSAC and TPS-RPM algorithms for non-rigid registration. We consider Scale Invariant Feature Transform (SIFT) [8] and Speeded-Up Robust Features (SURF) [1] as our features. Results are reported as comparing prior art with our method on a dataset that will be made publicly available. © 2011 ieee.

关键词： Cameras

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The design of intelligent crowd attention detection system based on face detection technology 13

The design of intelligent crowd attention detection system b...

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2017 13th ieee International conference on Electronic Measurement & Instruments (ICEMI)

作者： Luo Qiming Hou Ligang Xu Qiuyun Ye Tongyang Wang Jinhui Geng Shuqin VLSI and System Lab Beijing University of Technology Department of Electrical and Computer Engineering North Dakota State University

ISBN: (纸本)9781509050369;9781509050352

As a key technology in modern society, face detection has become an active subject in the field of pattern recognition and computer vision. In this paper, we propose some applications of analyzing crowd attention based on face detection technology and realize a crowd attention detection system using Haar-like features and Adaboost algorithm. The system consists of image acquisition module, face detection module, display module and data analysis module. At the same time, we adopt the method of empirical research. Using the camera, combined with software named AMcap, the system captures images of crowed during the display of a video regularly. Then, the system detects the faces which are being concerned about this attractive video in images, circling and counting them. In addition, the system displays the data change graph of the crowd face at different moments, and finally calculates the mathematical expected value of crowd attention for further processing.such as Big Data technology. After further processing. the system can obtain the data which reflects the degree of concern in a particular sector. Through the above experiment, Facts have proved that the system can easily, accurately and intuitively detect the crowd attention data and has great value in many sectors.

关键词： Face detection Crowd attention Detection system

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Computing the view orientations of random projections of asymmetric objects

Computing the view orientations of random projections of asy...

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conference on computer Vision and pattern recognition (CVPR)

作者： P.D. Lauren N. Nandhakumar Image Processing Center University of Virginia Charlottesville VA USA Department of Electrical Engineering University of Virginia Charlottesville VA USA

A method for determining the relative view orientation of randomly acquired projections of asymmetric objects is described. It extends the projection slice theorem by determining the relative orientation of projections by the location of lines of intersection among the Fourier transforms of the projections in 3D Fourier space. The complete algorithm is described, and its efficacy is demonstrated using real data.< >

关键词： Fourier transforms image reconstruction Electron beams image processing Magnetic resonance imaging Shape Computed tomography Humans Layout Electron microscopy

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Dynamic scene understanding for autonomous mobile robots.

Dynamic scene understanding for autonomous mobile robots.

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proceedings - CVPR '88: computer society conference on computer Vision and pattern recognition

作者： Burger, Wilhelm Bhanu, Bir Honeywell Systems & Research Cent Minneapolis MN USA

ISBN: (纸本)0818608625

An approach to the dynamic scene analysis is presented which departs from previous work by emphasizing a qualitative strategy of reasoning and modeling. Instead of refining a single quantitative description of the observed environment over time, multiple qualitative interpretations are maintained simultaneously. This offers superior robustness and flexibility over traditional numerical techniques which are often ill-conditioned and noise-sensitive. The main tasks of the authors' approach are (a) to detect and to classify the motion of individual objects in the scene, (b) to estimate the robot's egomotion, and (c) to derive the 3-D structure of the stationary environment. These three tasks strongly depend on each other. First, the direction of heading (i.e., translation) and rotation of the robot are estimated with respect to stationary locations in the scene. The focus of expansion (FOE) is not determined as particular image location, but as a region of possible FOE-locations called the fuzzy FOE. From this information, a rule-based system constructs and maintains a qualitative scene model. Results of this approach for real and synthetic imagery are presented.

关键词： image processing

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Continuously tracking and see-through occlusion based on a new hybrid synthetic aperture imaging model

Continuously tracking and see-through occlusion based on a n...

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作者： Yang, Tao Zhang, Yanning Tong, Xiaomin Zhang, Xiaoqiang Yu, Rui Shaanxi Key Laboratory of Speech and Image Information Processing School of Computer Science Northwestern Polytechnical University Xi'an 710129 China

ISBN: (纸本)9781457703942

Robust detection and tracking of multiple people in cluttered and crowded scenes with severe occlusion is a significant challenging task for many computer vision applications. In this paper, we present a novel hybrid synthetic aperture imaging model to solve this problem. The main characteristics of this approach include: (1) To the best of our knowledge, this algorithm is the first time to solve the occluded people imaging and tracking problem in a joint multiple camera synthetic aperture imaging domain. (2) A multiple model framework is designed to achieve seamless interaction among the detection, imaging and tracking modules. (3)In the object detection module, a multiple constraints based approach is presented for people localizing and ghost objects removal in a 3D foreground silhouette synthetic aperture imaging volume. (4) In the synthetic imaging module, a novel occluder removal based synthetic imaging approach is proposed to continuously obtain object clear image even under severe occlusion. (5) In the object tracking module, a camera array is used for robust people tracking in color synthetic aperture images. A network camera based hybrid synthetic aperture imaging system has been set up, and experimental results with qualitative and quantitative analysis demonstrate that the method can reliably locate and see people in challenge scene. © 2011 ieee.

关键词： Object detection

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