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484
Modeling the World from Internet Photo Collections
- INT J COMPUT VIS
, 2007
"... There are billions of photographs on the Internet, comprising the largest and most diverse photo collection ever assembled. How can computer vision researchers exploit this imagery? This paper explores this question from the standpoint of 3D scene modeling and visualization. We present structure-fro ..."
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Cited by 267 (6 self)
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There are billions of photographs on the Internet, comprising the largest and most diverse photo collection ever assembled. How can computer vision researchers exploit this imagery? This paper explores this question from the standpoint of 3D scene modeling and visualization. We present structure-from-motion and image-based rendering algorithms that operate on hundreds of images downloaded as a result of keyword-based image search queries like “Notre Dame ” or “Trevi Fountain.” This approach, which we call Photo Tourism, has enabled reconstructions of numerous well-known world sites. This paper presents these algorithms and results as a first step towards 3D modeling of the world’s well-photographed sites, cities, and landscapes from Internet imagery, and discusses key open problems and challenges for the research community.
Detailed real-time urban 3D reconstruction from video.
- IJCV,
, 2008
"... Abstract The paper presents a system for automatic, georegistered, real-time 3D reconstruction from video of urban scenes. The system collects video streams, as well as GPS and inertia measurements in order to place the reconstructed models in geo-registered coordinates. It is designed using curren ..."
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Cited by 185 (22 self)
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Abstract The paper presents a system for automatic, georegistered, real-time 3D reconstruction from video of urban scenes. The system collects video streams, as well as GPS and inertia measurements in order to place the reconstructed models in geo-registered coordinates. It is designed using current state of the art real-time modules for all processing steps. It employs commodity graphics hardware and standard CPU's to achieve real-time performance. We present the main considerations in designing the system and the steps of the processing pipeline. Our system extends existing algorithms to meet the robustness and variability necessary to operate out of the lab. To account for the large dynamic range of outdoor videos the processing pipeline estimates global camera gain changes in the feature tracking stage and efficiently compensates for these in stereo estimation without impacting the real-time performance. The required accuracy for many applications is achieved with a two-step stereo reconstruction process exploiting the redundancy across frames. We show results on real video sequences comprising hundreds of thousands of frames.
Visual odometry for ground vehicle applications
- Journal of Field Robotics
, 2006
"... We present a system that estimates the motion of a stereo head or a single moving camera based on video input. The system operates in real-time with low delay and the motion estimates are used for navigational purposes. The front end of the system is a feature tracker. Point features are matched bet ..."
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Cited by 155 (7 self)
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We present a system that estimates the motion of a stereo head or a single moving camera based on video input. The system operates in real-time with low delay and the motion estimates are used for navigational purposes. The front end of the system is a feature tracker. Point features are matched between pairs of frames and linked into image trajectories at video rate. Robust estimates of the camera motion are then produced from the feature tracks using a geometric hypothesize-and-test architecture. This generates motion estimates from visual input alone. No prior knowledge of the scene nor the motion is necessary. The visual estimates can also be used in conjunction with information from other sources such as GPS, inertia sensors, wheel encoders, etc. The pose estimation method has been applied successfully to video from aerial, automotive and handheld platforms. We focus on results obtained with a stereo-head mounted on an autonomous ground vehicle. We give examples of camera trajectories estimated in real-time purely from images over previously unseen distances (600 meters) and periods of time. 1.
Rgbd mapping: Using depth cameras for dense 3d modeling of indoor environments
- In RGB-D: Advanced Reasoning with Depth Cameras Workshop in conjunction with RSS
, 2010
"... Abstract RGB-D cameras are novel sensing systems that capture RGB images along with per-pixel depth information. In this paper we investigate how such cameras can be used in the context of robotics, specifically for building dense 3D maps of indoor environments. Such maps have applications in robot ..."
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Cited by 149 (13 self)
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Abstract RGB-D cameras are novel sensing systems that capture RGB images along with per-pixel depth information. In this paper we investigate how such cameras can be used in the context of robotics, specifically for building dense 3D maps of indoor environments. Such maps have applications in robot navigation, manipulation, semantic mapping, and telepresence. We present RGB-D Mapping, a full 3D mapping system that utilizes a novel joint optimization algorithm combining visual features and shape-based alignment. Visual and depth information are also combined for view-based loop closure detection, followed by pose optimization to achieve globally consistent maps. We evaluate RGB-D Mapping on two large indoor environments, and show that it effectively combines the visual and shape information available from RGB-D cameras. 1
Stable real-time 3d tracking using online and offline information
- IEEE Transactions on Pattern Analysis and Machine Intelligence
, 2004
"... We propose an efficient real-time solution for tracking rigid objects in 3D using a single camera that can handle large camera displacements, drastic aspect changes, and partial occlusions. While commercial products are already available for offline camera registration, robust online tracking remain ..."
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Cited by 113 (7 self)
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We propose an efficient real-time solution for tracking rigid objects in 3D using a single camera that can handle large camera displacements, drastic aspect changes, and partial occlusions. While commercial products are already available for offline camera registration, robust online tracking remains an open issue because many real-time algorithms described in the literature still lack robustness and are prone to drift and jitter. To address these problems, we have formulated the tracking problem in terms of local bundle adjustment and have developed a method for establishing image correspondences that can equally well handle short and widebaseline matching. We then can merge the information from preceding frames with that provided by a very limited number of keyframes created during a training stage, which results in a real-time tracker that does not jitter or drift and can deal with significant aspect changes. Computer vision, Real-time systems, Tracking. Index Terms I.
Modeling and recognition of landmark image collections using iconic scene graphs
- In ECCV
"... Abstract. This paper presents an approach for modeling landmark sites such as the Statue of Liberty based on large-scale contaminated image collections gathered from the Internet. Our system combines 2D appearance and 3D geometric constraints to efficiently extract scene summaries, build 3D models, ..."
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Cited by 104 (11 self)
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Abstract. This paper presents an approach for modeling landmark sites such as the Statue of Liberty based on large-scale contaminated image collections gathered from the Internet. Our system combines 2D appearance and 3D geometric constraints to efficiently extract scene summaries, build 3D models, and recognize instances of the landmark in new test images. We start by clustering images using low-dimensional global “gist” descriptors. Next, we perform geometric verification to retain only the clusters whose images share a common 3D structure. Each valid cluster is then represented by a single iconic view, and geometric relationships between iconic views are captured by an iconic scene graph. In addition to serving as a compact scene summary, this graph is used to guide structure from motion to efficiently produce 3D models of the different aspects of the landmark. The set of iconic images is also used for recognition, i.e., determining whether new test images contain the landmark. Results on three data sets consisting of tens of thousands of images demonstrate the potential of the proposed approach. 1
From structure-from-motion point clouds to fast location recognition
- In IEEE Conference on Computer Vision and Pattern Recognition (CVPR
, 2009
"... Efficient view registration with respect to a given 3D reconstruction has many applications like inside-out tracking in indoor and outdoor environments, and geo-locating images from large photo collections. We present a fast location recognition technique based on structure from motion point clouds. ..."
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Cited by 103 (10 self)
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Efficient view registration with respect to a given 3D reconstruction has many applications like inside-out tracking in indoor and outdoor environments, and geo-locating images from large photo collections. We present a fast location recognition technique based on structure from motion point clouds. Vocabulary tree-based indexing of features directly returns relevant fragments of 3D models instead of documents from the images database. Additionally, we propose a compressed 3D scene representation which improves recognition rates while simultaneously reducing the computation time and the memory consumption. The design of our method is based on algorithms that efficiently utilize modern graphics processing units to deliver real-time performance for view registration. We demonstrate the approach by matching hand-held outdoor videos to known 3D urban models, and by registering images from online photo collections to the corresponding landmarks. 1.
Two years of visual odometry on the Mars Exploration Rovers
- Journal of Field Robotics, Special Issue on Space Robotics
, 2007
"... NASA’s two Mars Exploration Rovers (MER) have successfully demonstrated a robotic Visual Odometry capability on another world for the first time. This provides each rover with accurate knowledge of its position, which allows it to autonomously detect and compensate for any unforeseen slip encountere ..."
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Cited by 98 (4 self)
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NASA’s two Mars Exploration Rovers (MER) have successfully demonstrated a robotic Visual Odometry capability on another world for the first time. This provides each rover with accurate knowledge of its position, which allows it to autonomously detect and compensate for any unforeseen slip encountered during a drive. It has enabled the rovers to drive safely and more effectively in highly-sloped and sandy terrains, and has resulted in increased mission science return by reducing the number of days required to drive into interesting areas. The MER Visual Odometry system comprises onboard software for comparing stereo pairs taken by the pointable mast-mounted 45 degree FOV Navigation cameras (NAVCAMs). The system computes an update to the 6 Degree Of Freedom rover pose (x, y, z, roll, pitch, yaw) by tracking the motion of autonomously-selected terrain features between two pairs of 256x256 stereo images. It has demonstrated good performance with high rates of successful convergence (97 % on Spirit, 95 % on Opportunity), successfully detected slip ratios as high as 125%, and measured changes as small as 2 mm, even while driving on slopes as high as 31 degrees. During the first two years of operations, Visual Odometry evolved from an “extra credit ” capability into a critical vehicle safety system. In this paper we describe our Visual Odometry algorithm, discuss several driving strategies that rely on it (including Slip Checks, Keep-out Zones, and Wheel Dragging), and summarize its results from the first two years of operations on Mars. 1
Outdoor slam using visual appearance and laser ranging.
- In Proc. IEEE International Conference on Robotics and Automation, (ICRA’06),
, 2006
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