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Multiview Geometry for Texture Mapping 2D Images Onto 3D Range Data

Multiview Geometry for Texture Mapping 2D Images Onto 3D Ran...

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conference on computer vision and pattern recognition (CVPR)

作者： Lingyun Liu I. Stamos Gene Yu G. Wolberg S. Zokai Department of Computer Science Hunter College and Graduate Center of CUNY NY USA Department of Computer Science City College슠of New York NY USA Brainstorm Technology NY USA

The photorealistic modeling of large-scale scenes, such as urban structures, requires a fusion of range sensing technology and traditional digital photography. This paper presents a system that integrates multiview geometry and automated 3D registration techniques for texture mapping 2D images onto 3D range data. The 3D range scans and the 2D photographs are respectively used to generate a pair of 3D models of the scene. The first model consists of a dense 3D point cloud, produced by using a 3D-to-3D registration method that matches 3D lines in the range images. The second model consists of a sparse 3D point cloud, produced by applying a multiview geometry (structure-from-motion) algorithm directly on a sequence of 2D photographs. This paper introduces a novel algorithm for automatically recovering the rotation, scale, and translation that best aligns the dense and sparse models. This alignment is necessary to enable the photographs to be optimally texture mapped onto the dense model. The contribution of this work is that it merges the benefits of multiview geometry with automated registration of 3D range scans to produce photorealistic models with minimal human interaction. We present results from experiments in large-scale urban scenes.

关键词： Geometry Layout Large-scale systems Cameras computer science Educational institutions Digital photography Clouds Solid modeling Image sensors

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Segmentation of Vessels Using Weighted Local Variances and an Active contour Model

Segmentation of Vessels Using Weighted Local Variances and a...

引用

ieee computer society conference on computer vision and pattern recognition Workshops (CVPRW)

作者： W.K. Law A.C.S. Chung Lo Kwee-Seong Medical Image Analysis Laboratory Department of Computer Science Hong Kong University of Science and Technology Hong Kong China

Performing segmentation of vasculature with blurry and low contrast boundaries in noisy images is a challenging problem. This paper presents a novel approach to segmenting blood vessels using weighted local variances and an active contour model. In this work, the vessel boundary orientation is estimated locally based on the orientation that minimizes the weighted local variance. Such estimation is less sensitive to noise compared with other common approaches. The edge clearness is measured by the ratio of weighted local variances obtained along different orientations. It is independent of the edge intensity contrast and capable of locating weak boundaries. Integrating the orientation and clearness of edges, an active contour model is employed to align contours that match the contour tangent direction and edge orientation. The proposed method is validated by two synthetic images and two real cases. It is experimentally shown that our method is suitable for dealing with noisy images which consist of structures having blurry and low contrast boundaries, such as blood vessels.

关键词： Active contours Image segmentation Biomedical imaging Image edge detection Blood vessels Angiography Laboratories computer science Active noise reduction Level set

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Fast Image Motion Computation on an Embedded computer

Fast Image Motion Computation on an Embedded Computer

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ieee computer society conference on computer vision and pattern recognition Workshops (CVPRW)

作者： X. Lu R. Manduchi University of California Santa Cruz USA

Wireless, battery-powered camera networks are becoming of interest for surveillance and monitoring applications. The computational power of these platforms is often limited in order to reduce energy consumption. Among the visual tasks that the onboard processor may be required to perform, motion analysis is one of the most basic and relevant. Knowledge of the direction of motion and velocity of a moving body may be used to take actions such as sending an alarm or triggering other camera nodes in the network. We present a fast algorithm for identifying moving areas in an image and computing the average velocity in such areas. The algorithm, which was implemented and tested on a Crossbow Stargate embedded platform, is comprised of three stages. First, local differential measurements are used to determine an initial labeling of image blocks. A total least squares approach is proposed, with fast implementation inspired by the work of Benedetti and Perona. Then, belief propagation is used to impose spatial coherence and resolve aperture effect inherent in textureless areas. Finally, the velocity of the resulting blobs is estimated via least squares regression. A detailed analysis of timing and power consumption characteristics of this algorithm is also presented.

关键词： Embedded computing Cameras Energy consumption Surveillance computerized monitoring Application software computer applications Motion analysis Testing Labeling

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Content-Based Dynamic 3D Mosaics

Content-Based Dynamic 3D Mosaics

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ieee computer society conference on computer vision and pattern recognition Workshops (CVPRW)

作者： Zhigang Zhu Hao Tang Department of Computer Science City College of New York New York NY USA

We propose a content-based 3D mosaic (CB3M) representation for long video sequences of 3D and dynamic scenes captured by a camera on a mobile platform. After a set of parallel-perspective (pushbroom) mosaics with varying viewing directions is generated, a multi-view, segmentation-based stereo matching algorithm is applied to extract parametric representations of the color, structure and motion of the dynamic and/or 3D objects in urban scenes. We use the fact that all the static objects obey the epipolar geometry of pushbroom stereo, whereas an independent moving object either violates the epipolar geometry if the motion is not in the direction of sensor motion or exhibits unusual 3D structures. The CB3M is a highly compressed visual representation for a very long video sequence of a dynamic 3D scene. More importantly, the CB3M representation has object contents of both 3D and motion. Experimental results are given for the CB3M construction for both simulated and real video sequences.

关键词： Layout Cameras Video sequences Vehicle dynamics Geometry Video compression Streaming media Data mining computer science Cities and towns

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vision-Based Projection-Handwriting Integration in Classroom

Vision-Based Projection-Handwriting Integration in Classroom

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ieee computer society conference on computer vision and pattern recognition Workshops (CVPRW)

作者： Weihong Li Hao Tang Zhigang Zhu Graduate Center City University of New York New York NY USA City College City University of New York New York NY USA Graduate Center & City College City University of New York New York NY USA

A projector based presentation and a whiteboard handwriting capture system, when monitored by a camera, could provide a better means to present a lecture in a classroom and later to deliver more effective e-lectures for off-campus students. When the PowerPoint© (PPT) slides are projected on the whiteboard where the instructor annotates, modifies, or expands the PPT presentation, geometrically registering high-resolution images from the two sources yields high quality digital presentations. Since the two sources do not share the same materials, one with printing notes and the other with handwriting notes, a digital camera is used as a bridge to align the two sources, as well as to record the whole lecture. We present a hybrid registration approach to align the PPT and handwriting images and then propose a coarse-to-fine content matching method to register handwriting contents captured by the video camera and the whiteboard capture system. We also show an integrated user-customized presentation system to provide students better lecturing context. Experimental results are presented to validate our approach, and future research directions are also discussed.

关键词： Cameras Cities and towns Educational institutions computer vision Switches Video sharing Sensor systems Ink Timing HTML

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A Class of Detection Filters for Targets and Anomalies in Multispectral / Hyperspectral Imagery

A Class of Detection Filters for Targets and Anomalies in Mu...

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ieee computer society conference on computer vision and pattern recognition Workshops (CVPRW)

作者： S.A. Robila Montclair State University Montclair NJ USA

In this paper we present a class of detection filters based on variations of the spectral screening. Spectral screening is a technique used in reducing the multispectral / hyperspectral data to a representative subset of spectra. The subset is formed such that any two spectra in it are dissimilar and, for any spectrum in the original image cube, there is a similar spectrum in the subset. Spectral screening is performed in a sequential manner, at each step, the subset being increased with a spectrum dissimilar from all the spectra already selected. The procedure, using the spectral angle as similarity measure is employed in a variety of algorithms for linear unmixing and data compression. We modified the algorithm such that at the selection step the spectrum with the largest distance from the set is selected. While not introducing additional computational complexity, the Maximum Spectral Screening (MSS) algorithm ensures that the overlap among the representatives is minimized. MSS is further improved by choosing as first spectra the one with the largest distance to the diagonal, thus transforming the screening into a deterministic process. Second, we investigated the alternative approach where at each step the spectra with the smallest distance (but larger than a threshold value) is selected (Minimum Spectral Screening mSS). The detection filters were obtained as the classification projector matrices based on the spectral subset. The developed algorithms were tested on HYDICE hyperspectral data using the spectral angle and the spectral information divergence. The results indicate that MSS outperforms regular spectral screening detection and mSS.

关键词： Filters Hyperspectral imaging Sections Pixel Detectors Data mining USA Councils computer vision pattern recognition conferences

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Transitivity-based Removal of Correspondence Outliers for Motion Analysis

Transitivity-based Removal of Correspondence Outliers for Mo...

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ieee computer society conference on computer vision and pattern recognition Workshops (CVPRW)

作者： A. Robles-Kelly Y. Moses NICTA Canberra ACT Australia School of Computer Science Interdisciplinary Center Herzliya Israel

In this paper we address the problem of removing correspondence outliers in a sequence of images. The input to the system is a set of putative matches which are based upon image-feature similarity. Classical methods for outlier removal, such as RANSAC-based approaches, assume consistency and rigidity in the scene motion between two or three frames in the sequence. Here we propose a novel method for removing correspondence outliers that does not depend on such assumptions. Our method is based on the observation that correspondence is an equivalence relation, and, hence, transitivity must hold between corresponding features in different frames. We impose consistency on the transitivity by representing the matching information as a weighted graph with positive and negative edge-weights. Consistency is then enforced by partitioning the nodes in the graph so as to remove edges corresponding to falsepositive correspondences. The clustering algorithm is of spectral nature and can handle graphs whose edge-weights are non-positive. Our method is a general one that can be used for purposes of outlier removal from correspondences between any entities whose putative matches imply equivalence relations. We illustrate the utility of the method for purposes of outlier removal on a real-world image sequence and compare our results with those yield using an alternative.

关键词： Motion analysis Australia Layout Image sequences Tracking Shape computer science Clustering algorithms Partitioning algorithms pattern matching

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Consistency of location and gradient judgments of visually-interpolated contours

Consistency of location and gradient judgments of visually-i...

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ieee computer society conference on computer vision and pattern recognition Workshops (CVPRW)

作者： J.M. Fulvio M. Singh L.T. Maloney Psychology New York University New York NY USA Psychology & Cognitive Science Rutgers University-New Brunswick Piscataway NJ USA Psychology & Neural Science New York University New York NY USA

We report two experiments assessing how observers interpolate partly-occluded contours induced by pairs of line segments that disappeared behind an occluder. On each trial observers iteratively adjusted the location and orientation of a short line probe that could be moved vertically within the region of occlusion. They were instructed to set the line probe to be tangent to the occluded contour. The line probe could appear at one of six horizontal offsets and the inducer pairs on some trials were relatable (the inducers could be joined by a smooth curve without a point of inflection) and on other trials non-relatable. We interpreted the settings as estimates of the location and gradient (slope) of the contour in the region of occlusion. We tested whether the resulting visual estimates of location and gradient were consistent with any single smooth contour. When inducers were relatable, estimates of location and gradient were mutually consistent for all observers and could be modeled as polynomials of 5^th or lower degree. When the inducers were non-relatable, the consistency of location and gradient settings deteriorated, indicating that there can be no single smooth curve that accounts for observers’ judgments. We discuss the implication of these results for models of human visual interpolation.

关键词： Interpolation Psychology computer vision pattern recognition conferences Shape measurement Displays Turning Cognitive science Testing

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Online Tracking of Migrating and Proliferating Cells Imaged with Phase-Contrast Microscopy

Online Tracking of Migrating and Proliferating Cells Imaged ...

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ieee computer society conference on computer vision and pattern recognition Workshops (CVPRW)

作者： Kang Li E.D. Miller L.E. Weiss P.G. Campbell T. Kanade Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA USA Department of Biomedical Engineering Carnegie Mellon University Pittsburgh PA USA Robotics Institute Carnegie Mellon University Pittsburgh PA USA Institute for Complex Engineered Systems Carnegie Mellon University Pittsburgh PA USA

Automated visual-tracking of cell population in vitro using phase-contrast time-lapse microscopy is vital for the quantitative and systematic study of cell behaviors, including spatiotemporal quantification of migration, proliferation, and apoptosis. The low image quality, high and varying density of the cell culture, and the complexity of cell behaviors pose many challenges to existing tracking techniques. This paper presents a fully-automated multitarget tracking system that can simultaneously track hundreds of cells and efficiently cope with these challenges. The approach exploits a fast topology-constrained level-set method in conjunction with a stochastic motion filter, with a careful formulation that makes it suitable for real-time tracking during acquisition. Our methodology was applied to human tissue cell tracking in vitro under various imaging conditions and yielded a 88.4% tracking accuracy.

关键词： Microscopy Object detection Biomedical engineering In vitro Stochastic processes Filters Tracking Extracellular Shape Detectors

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BICIR:Boundary-Constrained Inverse Consistent Image Registration Using WEB-Splines

BICIR:Boundary-Constrained Inverse Consistent Image Registra...

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ieee computer society conference on computer vision and pattern recognition Workshops (CVPRW)

作者： D. Kumar Xiujuan Geng E.A. Hoffman G.E. Christensen Department of Electrical and Computer Engineering University of Iowa Iowa IA USA Department of Radiology University of Iowa Iowa IA USA

We present a new registration method called boundaryconstrained inverse consistent image registration (BICIR). This method is novel because it performs boundary constrained intensity based image registration by combining surface- and intensity-based registration. The method registers a region of interest and ignores everything outside the region eliminating interference caused by surrounding regions. The boundaries of the two objects are first registered using the transitive inverse-consistent manifold registration (TICMR) described in [4]. This provides the boundary conditions, which are used to compute the displacement over the object using the Element Free Galerkin Method (EFGM). The EFGM solution is used as an initialization and is fine-tuned using the intensity information inside the object. The transformations are represented with shape specific basis functions that have local support. These basis functions are defined only over the region of interest and help improve the computational performance. The BICIR method was tested for a number of 2-dimensional test images. The method was validated using the similarity cost, relative overlap and inverse consistency error.

关键词： Image registration Registers Cities and towns Moment methods Shape Testing Radiology Interference constraints Interference elimination Boundary conditions

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