2845021
Incremental motion estimation through modified bundle adjustment
An incremental motion estimation scheme for long image sequence analysis is introduced. It applies to a sliding window of triplet images and maintains local motion consistency without resort to post-concatenation. This is possible thanks to our newly developed local process called three-view partial bundle adjustment. Unlike previous approaches that rely only on point matches across three or more views, our local process also takes into account all available two-view matches, leading to more accurate motion estimation. For sparse image sequences, two-view matches are very reliable and it becomes even more important to use them since the number of matches across more views decreases quickly. In this case, our incremental method can produce results very close to those obtained with a global bundle adjustment but in a fraction of time. Experiments with both synthetic and real data have been conducted to compare the proposed technique with other techniques, and have shown our technique to be clearly superior.
36184486
Image-Based Surface Detail Transfer
We present a novel technique, called Image-Based Surface Detail Transfer, to transfer geometric details from one surface to another with simple 2D image operations. The basic observation is that, without knowing its 3D geometry, geometric details (local deformations) can be extracted from a single image of an object in a way independent of its surface reflectance, and furthermore, these geometric details can be transferred to modify the appearance of other objects directly in images. We show examples including surface detail transfer between real objects, as well as between real and synthesized objects.
2276524
Automatic Business Card Scanning with a Camera
In this paper, we present a system to automatically extract, rectify and enhance business card images. First the business card image patch is automatically segmented by minimizing a novel local-global variational energy. Second a quadrangle is fitted to the segmented image patch. With the four corner points of the quadrangle, we then estimate the physical aspect ratio of the business card and obtain a homography to rectify the quadrangle back to rectangular shape. We finally enhance the contrast of the rectified business card image using a S-shaped curve. Extensive experiments demonstrated the efficacy and robustness of our system.
28801152
Remote Collaboration on Physical Whiteboards
A whiteboard provides a large shared space for the participants to focus their attention and express their ideas, and is therefore a great collaboration tool for information workers. However, it has several limitations; notably, the contents on the whiteboard are hard to archive or share with people who are not present in the discussions. This paper presents our work in developing tools to facilitate collaboration on physical whiteboards by using a camera and a microphone. In particular, our system allows a user to take notes of a whiteboard meeting when he/she wants or in an automatic way, to transmit the whiteboard content to remote participants in real time and in an efficient way, and to archive the whole whiteboard session for efficient post-viewing. Our system can be retrofit to any existing whiteboard. With the help of a camera and a microphone, we are effectively bridging the physical and digital worlds.
8951856
Model-based head pose tracking with stereovision
We present a robust model-based stereo head tracking algorithm that operates in real time on a commodity PC. The use of an individualized three-dimensional head model, coupled with the epipolar constraint from the stereo image pair greatly improves the robustness of the tracking. Experimental results have shown that our method is able to track all the six degrees of freedom of the rigid part of head motions, over an extended period of time, in the presence of large angular and translational head motions, partial occlusions, and/or dramatic facial expression changes. Applications include human-computer interaction and eye-gaze correction for videoconferencing.
18016173
Corner guided curve matching and its application to scene reconstruction
Corners and curves are important image features in many vision-based applications. Corners are usually more stable and easier to match than curves, while curves contain richer information of scene structure. In previously work, corners are often used to recover the epipolar geometry between two views, which is then used in curve matching to reduce the search space. However, information of the scene structure contained in this set of matched corners is ignored. In this paper we present a curve matching algorithm that is guided by a set of matched corners. Within a probabilistic framework, the role of the corner guidance is explicitly defined by a set of similarity-invariant unary measurements and by a similarity function. The similarity function provides stronger capability of resolving matching ambiguity than the epipolar constraint, and is integrated into a relaxation scheme to reduce computational complexity and improve accuracy of curve matching. Experimental results clearly demonstrate the benefit of integrating corner matches into the curve matching procedure.
5858737
A Robust Technique for Matching two Uncalibrated Images Through the Recovery of the Unknown Epipolar Geometry
Abstract This paper proposes a robust approach to image matching by exploiting the only available geometric constraint, namely, the epipolar constraint. The images are uncalibrated, namely the motion between them and the camera parameters are not known. Thus, the images can be taken by different cameras or a single camera at different time instants. If we make an exhaustive search for the epipolar geometry, the complexity is prohibitively high. The idea underlying our approach is to use classical techniques (correlation and relaxation methods in our particular implementation) to find an initial set of matches, and then use a robust technique—the Least Median of Squares (LMedS)—to discard false matches in this set. The epipolar geometry can then be accurately estimated using a meaningful image criterion. More matches are eventually found, as in stereo matching, by using the recovered epipolar geometry. A large number of experiments have been carried out, and very good results have been obtained. Regarding the relaxation technique, we define a new measure of matching support, which allows a higher tolerance to deformation with respect to rigid transformations in the image plane and a smaller contribution for distant matches than for nearby ones. A new strategy for updating matches is developed, which only selects those matches having both high matching support and low matching ambiguity. The update strategy is different from the classical “winner-take-all”, which is easily stuck at a local minimum, and also from “loser-take-nothing”, which is usually very slow. The proposed algorithm has been widely tested and works remarkably well in a scene with many repetitive patterns.
12306777
A single spike model of predictive coding
7151005
On-Line Optimal Wavelength Assignment in WDM Networks With Shared Wavelength Converter Pool
In this paper, we study on-line wavelength assignment in wavelength-routed WDM networks under both unicast and multicast traffic where nodes in the networks have wavelength conversion ability. Since wavelength converters are still expensive and difficult to implement, we consider the case where nodes in networks have only a limited number of converters that are shared by all input channels. We study the problem of setting up connections in such networks using minimum number of wavelength converters. For unicast traffic, we first study the problem of setting up a lightpath on a given link-path with minimum number of conversions. We give a simple algorithm that solves it in O(tk) time where t is the number of links on the path and k is the number of wavelengths per fiber, as compared to the best known existing method that needs to construct an auxiliary graph and apply the Dijkstra's algorithm. We also consider the problem of setting up a lightpath while using wavelength converters at nodes with fewer available converters only when necessary, and give an O(tk) time algorithm. We then generalize this technique to WDM networks with arbitrary topologies and give an algorithm that sets up an optimal lightpath network-wide in O(Nk+Lk) time, where N and L are the number of nodes and links in the network, respectively. We also consider multicast traffic in this paper. Finding an optimal multicast light-tree is known to be NP-hard and is usually solved by first finding a link-tree then finding a light-tree on the link-tree. Finding an optimal link-tree is also NP-hard and has been extensively studied. Thus, we focus on the second problem which is to set up a light-tree on a given link-tree with minimum number of conversions. We propose a new multicast conversion model with which the output of the wavelength converter is split-table to save the usage of converters. We show that under this model the problem of setting up an optimal light-tree is NP-hard and then give efficient heuristics to solve it approximately
1150626
A Flexible New Technique for Camera Calibration
We propose a flexible technique to easily calibrate a camera. It only requires the camera to observe a planar pattern shown at a few (at least two) different orientations. Either the camera or the planar pattern can be freely moved. The motion need not be known. Radial lens distortion is modeled. The proposed procedure consists of a closed-form solution, followed by a nonlinear refinement based on the maximum likelihood criterion. Both computer simulation and real data have been used to test the proposed technique and very good results have been obtained. Compared with classical techniques which use expensive equipment such as two or three orthogonal planes, the proposed technique is easy to use and flexible. It advances 3D computer vision one more step from laboratory environments to real world use.
1852867
Semantic repository modeling in image database
This work is about content based image database retrieval, focusing on developing a classification based methodology to address semantics-intensive image retrieval. With self organization map based image feature grouping, a visual dictionary is created for color, texture, and shape feature attributes, respectively. Labeling each training image with the keywords in the visual dictionary, a classification tree is built. Based on the statistical properties of the feature space we define a structure, called /spl alpha/-semantics graph, to discover the hidden semantic relationships among the semantic repositories embodied in the image database. With the /spl alpha/-semantics graph, each semantic repository is modeled as a unique fuzzy set to explicitly address the semantic uncertainty and the semantic overlap existing among the repositories in the feature space. A retrieval algorithm combining the classification tree with the fuzzy set models to deliver semantically relevant image retrieval is provided. The experimental evaluations have demonstrated that the proposed approach models the semantic relationships effectively and outperforms a state-of-the-art content based image retrieval system in the literature both in effectiveness and efficiency.