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A Min-Cover Approach for Finding Salient Curves

A Min-Cover Approach for Finding Salient Curves

引用

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

作者： P. Felzenszwalb D. McAllester University of Chicago USA TTI-Chicago

We consider the problem of deriving a global interpretation of an image in terms of a small set of smooth curves. The problem is posed using a statistical model for images with multiple curves. Besides having important applications to edge detection and grouping the curve finding task is a special case of a more general problem, where we want to explain the whole image in terms of a small set of objects. We describe a novel approach for estimating the content of scenes with multiple objects using a min-cover framework that is simple and powerful. The min-cover problem is NP-hard but there is a good approximation algorithm that sequentially selects objects minimizing a "cost per pixel" measure. In the case of curve detection we use a type of best-first search to quickly find good curves for the covering algorithm. The method integrates image data over long curves without relying on binary feature detection. We have applied the curve detection method for finding object boundaries in natural scenes and measured its performance using the Berkeley segmentation dataset.

关键词： Layout Object detection Costs Approximation algorithms Image segmentation Image edge detection computer vision Gray-scale Color Object recognition

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An FPGA-Based Verification Framework for Real-Time vision Systems

An FPGA-Based Verification Framework for Real-Time Vision Sy...

引用

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

作者： G. van der Wal F. Brehm M. Piacentino J. Marakowitz E. Gudis A. Sufi J. Montante Embedded Vision Systems Sarnoff Corporation Princeton NJ USA

Field-Programmable Gate Arrays (FPGAs) have become a mainstay in the digital electronics world both for the ease of implementation as well as their inherent usefulness in incrementally refining hardware designs. When moving to an Application Specific Integrated Circuit (ASIC) or System on a Chip (SoC), verification becomes a very time consuming process, with virtually no room for error. As a result, a variety of methods have been devised to decrease the risk when creating an ASIC or SoC. We describe a hardware and software framework for testing real-time vision algorithms for lowering the uncertainty in FPGA and SoC development, while reducing the SoC verification time. The framework benefits from hardware and software verification, ease of reconfiguration for testing multiple vision algorithms, and an iterative hardware/ software co-design.

关键词： Real time systems Machine vision Hardware System-on-a-chip Field programmable gate arrays Application specific integrated circuits Software testing Software algorithms Iterative algorithms Circuit testing

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3D Building Detection and Modeling from Aerial LIDAR Data

3D Building Detection and Modeling from Aerial LIDAR Data

引用

conference on computer vision and pattern recognition (CVPR)

作者： V. Verma R. Kumar S. Hsu Sarnoff Corporation USA Canesta Inc. USA

This paper presents a method to detect and construct a 3D geometric model of an urban area with complex buildings using aerial LIDAR (Light Detection and Ranging) data. The LIDAR data collected from a nadir direction is a point cloud containing surface samples of not only the building roofs and terrain but also undesirable clutter from trees, cars, etc. The main contribution of this work is the automatic recognition and estimation of simple parametric shapes that can be combined to model very complex buildings from aerial LIDAR data. The main components of the detection and modeling algorithms are (i) Segmentation of roof and terrain points. (ii) Roof topology Inference. We introduce the concept of a roof-topology graph to represent the relationships between the various planar patches of a complex roof structure. (iii) Parametric roof composition. Simple parametric roof shapes that can be combined to create a complex roof structure of a building are recognized by searching for sub-graphs in its roof-topology graph. (iv) Terrain Modeling. The terrain is identified and modeled as a triangulated mesh. Finally, we provide experimental results that demonstrate the validity of our approach for rapid and automatic building detection and geometric modeling with real LIDAR data. We are able to model cities and other urban areas at the rate of about 10 minutes per sq. mile on a low-end PC.

关键词： Laser radar Buildings Shape Solid modeling Urban areas Cities and towns Image reconstruction Urban planning computer vision Image edge detection

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A Camera-Based Energy Relaxation Framework to Minimize Color Artifacts in a Projected Display

A Camera-Based Energy Relaxation Framework to Minimize Color...

引用

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

作者： N. Sanders C. Jaynes University of Kentucky Lexington KY USA

We introduce a technique to automatically correct color inconsistencies in a display composed of one or more digital light projectors (DLP). The method is agnostic to the source of error and can detect and address color problems from a number of sources. Examples include inter- and intra-projector color differences, display surface markings, and environmental lighting differences on the display. In contrast to methods that discover and map all colors into the greatest common color space, we minimize local color discontinuities to create color seamlessness while remaining tolerant to significant color error. The technique makes use of a commodity camera and high-dynamic range sensing to measure color gamuts at many different spatial locations. A differentiable energy function is defined that combines both a smoothness and data term. This energy function is globally minimized through the successive application of projective warps defined using gradient descent. At convergence the warps can be applied at runtime to minimize color defects in the display. The framework is demonstrated on displays that suffer from several sources of color

关键词： Cameras Color Lighting computer displays USA Councils Current measurement Particle measurements Parametric statistics Calibration computer vision

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Globally Optimal Interactive Boundary Extraction Using Markov Chain Modeling

Globally Optimal Interactive Boundary Extraction Using Marko...

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

作者： C. Pavlopoulou A. Kak School of Electrical and Computer Engineering Purdue University USA

We present a novel boundary-based (discontinuity tracking) hierarchical statistical criterion to address the interactive contour extraction problem. Our criterion relies on a Markov Chain representation of the boundary and can be efficiently optimized using Dijkstra’s algorithm for solving the shortest paths problem. Unlike other criteria optimized with Dijkstra’s algorithm, ours is capable of extracting geometrically complex boundaries even when the features incorporated in the objective function are based only on user markings on a small part of the image. The critical quantity in our criterion that yields the above-mentioned results is a normalization factor that boosts the probability of a particular boundary segment based on the candidate boundary segments in its vicinity. Although similar in spirit to the technique of non-maximum suppression routinely employed in edge detection, our method boosts gradually the probability of a particular segment given its surroundings using windows of increasing size in a hierarchical fashion.

关键词： Humans Probability Shortest path problem Image segmentation Image edge detection computer vision Dynamic programming Focusing Bayesian methods Smoothing methods

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Learning Non-Metric Partial Similarity Based on Maximal Margin Criterion

Learning Non-Metric Partial Similarity Based on Maximal Marg...

引用

conference on computer vision and pattern recognition (CVPR)

作者： Xiaoyang Tan Songcan Chen Jun Li Zhi-Hua Zhou Department of Computer Science and Engineering Nanjing University of Aeronautics & Astronautics Nanjing China National Laboratory for Novel Software Technology Nanjing University Nanjing China

ISBN: (纸本)0769525970

The performance of many computer vision and machine learning algorithms critically depends on the quality of the similarity measure defined over the feature space. Previous works usually utilize metric distances which are ofen epistemologically different from the perceptual distance of human beings. In this paper a novel non-metric partial similarity measure is introduced, which is born to automatically capture the prominent partial similarity between two images while ignoring the confusing unimportant dissimilarity. This measure is potentially useful in face recognition since it can help identify the inherent intra-personal similarity and thus reducing the influence caused by large variations such as expression and occlusions. Moreover; to make this method practical, this paper proposes an automatic and class-dependent similarity threshold setting mechanism based on the maximal margin criterion, and uses a Self- Organization Map-based embedding technique to alleviate the computational problem. Experimental results show the feasibility and effectiveness of the proposed method.

关键词： Extraterrestrial measurements Clustering algorithms computer vision Humans pattern recognition Image matching Space technology Image databases Euclidean distance Robustness

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3D Reconstruction of Background and Objects Moving on Ground Plane Viewed from a Moving Camera

3D Reconstruction of Background and Objects Moving on Ground...

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conference on computer vision and pattern recognition (CVPR)

作者： Chang Yuan G. Medioni Institute of Robotics and Intelligent Systems University of Southern California Los Angeles CA USA

We present a novel method to obtain a 3D Euclidean reconstruction of both the background and moving objects in a video sequence. We assume that, multiple objects are moving rigidly on a ground plane observed by a moving camera. The video sequence is first segmented into static background and motion blobs by a homography-based motion segmentation method. Then classical "Structure from Motion" (SfM) techniques are applied to obtain a Euclidean reconstruction of the static background. The motion blob corresponding to each moving object is treated as if there were a static object observed by a hypothetical moving camera, called a "virtual camera". This virtual camera shares the same intrinsic parameters with the real camera but moves differently due to object motion. The same SfM techniques are applied to estimate the 3D shape of each moving object and the pose of the virtual camera. We show that the unknown scale of moving objects can be approximately determined by the ground plane, which is a key contribution of this paper. Another key contribution is that we prove that the 3D motion of moving objects can be solved from the virtual camera motion with a linear constraint imposed on the object translation. In our approach, a planartranslation constraint is formulated: "the 3D instantaneous translation of moving objects must be parallel to the ground plane". Results on real-world video sequences demonstrate the effectiveness and robustness of our approach.

关键词： computer vision Image reconstruction Video sequences Motion segmentation Shape Robot vision systems Intelligent robots Motion estimation Smart cameras Intelligent systems

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Adaptive Environment Map for Relighting: Using Cameras and Projected Light

Adaptive Environment Map for Relighting: Using Cameras and P...

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

作者： Hyunjung Shim Tsuhan Chen Carnegie Mellon University Pittsburgh PA USA

Scene relighting has found applications in many areas, from movie special effects to building immersive environments. In this paper, we present a framework to render a scene under any prescribed lighting environments. First, we propose a 3D scanner that captures the scene geometry and reflectance simultaneously, by effectively using an uncalibrated camera, and light and shadows projected from a controlled lighting plane onto the scene. Then, a large camera array, composed of 48 cameras forming a planar array, is built to capture a lighting environment as a 4D incident light field. With the scene properties captured by the 3D scanner, and the lighting environment captured by the camera array, we can then relight the scene using a technique we develop, called the adaptive environment map (AEM). AEM, which fully describes the lighting environment including both spatial and directional variations, can render more realistic relighting results than existing techniques in literature, as shown in extensive experiments.

关键词： Cameras Layout Reflectivity Geometry Optical arrays Geometrical optics Stereo vision Monitoring computer vision Surface reconstruction

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Measure Locally, Reason Globally: Occlusion-sensitive Articulated Pose Estimation

Measure Locally, Reason Globally: Occlusion-sensitive Articu...

引用

conference on computer vision and pattern recognition (CVPR)

作者： L. Sigal M.J. Black Department of Computer Science Brown University Providence RI USA

Part-based tree-structured models have been widely used for 2D articulated human pose-estimation. These approaches admit efficient inference algorithms while capturing the important kinematic constraints of the human body as a graphical model. These methods often fail however when multiple body parts fit the same image region resulting in global pose estimates that poorly explain the overall image evidence. Attempts to solve this problem have focused on the use of strong prior models that are limited to learned activities such as walking. We argue that the problem actually lies with the image observations and not with the prior. In particular, image evidence for each body part is estimated independently of other parts without regard to self-occlusion. To address this we introduce occlusion-sensitive local likelihoods that approximate the global image likelihood using per-pixel hidden binary variables that encode the occlusion relationships between parts. This occlusion reasoning introduces interactions between non-adjacent body parts creating loops in the underlying graphical model. We deal with this using an extension of an approximate belief propagation algorithm (PAMPAS). The algorithm recovers the real-valued 2D pose of the body in the presence of occlusions, does not require strong priors over body pose and does a quantitatively better job of explaining image evidence than previous methods.

关键词： Biological system modeling Humans Kinematics Graphical models Tree graphs Space exploration computer science Inference algorithms Legged locomotion Belief propagation

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Feature-level Fusion for Object Segmentation using Mutual Information

Feature-level Fusion for Object Segmentation using Mutual In...

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

作者： V. Sharma J.W. Davis Department of Computer Science and Engineering Ohio State Uinversity Columbus OH USA

We present a new feature-level image fusion technique for object segmentation based on mutual information. Using object regions roughly detected from one sensor as input, the proposed technique extracts relevant information from another to complete the segmentation. First, a contourbased feature representation is presented that implicitly captures object shape. The notion of relevance across sensor modalities is then defined using mutual information computed based on the affinity between contour features. Finally a heuristic selection scheme is proposed to identify the set of contour features having the highest mutual information with the input object regions. The approach works directly from the input image pair without relying on a training phase. Results are presented for segmenting people from background, and quantitatively evaluated.

关键词： Object segmentation Mutual information Sensor phenomena and characterization Image fusion Image segmentation Sensor fusion Object detection Image sensors Data mining Shape

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