12105004
New Measurements and Corner-Guidance for Curve Matching with Probabilistic Relaxation
Reliable curve matching is a difficult yet important problem in many vision-based applications including image-based modeling. We describe in this paper two aspects of our research in this area: a new algorithm for curve matching (including lines) within a probabilistic relaxation framework, and an approach of incorporating previously matched points/corners to guide curve matching. We propose similarity-invariant unary and binary measurements suitable for curves, and introduce an additional measurement to model the uncertainty of the binary measurements. The uncertainty measure is proven to be very important in computing the matching support from neighboring matches. We also show how to use a set of previously matched points/corners to guide the curve matching. The role of the corner guidance is explicitly modeled by a set of unary measurements and a similarity function under the same relaxation framework. Preprocessing techniques contributing to the success of our curve matching techniques are also developed and discussed. Experiments with complex real scenes show that the rate of correct matching is higher than 98%.
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.
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.
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.
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.
1383532
New directions in the theory of identification via channels
Studies two problems in the theory of identification via channels. The first problem concerns the identification via channels with noisy feedback. Whereas for Shannon's transmission problem the capacity of a discrete memoryless channel does not change with feedback, it is known that the identification capacity is affected by feedback. The authors study its dependence on the feedback channel. They prove both, a direct and a converse coding theorem. Although a gap exists between the upper and lower bounds provided by these two theorems, the known result for channels without feedback and the known result for channels with complete feedback, are both special cases of these two new theorems, because in these cases the bounds coincide. The second problem is the identification via wiretap channels. A secrecy identification capacity is defined for the wiretap channel. A "dichotomy theorem" is proved which says that the second-order secrecy identification capacity is the same as Shannon's capacity for the main channel as long as the secrecy transmission capacity of the wiretap channel is not zero, and zero otherwise. Equivalently, one can say that the identification capacity is not lowered by the presence of a wiretapper as long as 1 bit can be transmitted (or identified) correctly with arbitrarily small error probability. This is in strong contrast to the case of transmission. >
9330795
Application-specific instruction generation for configurable processor architectures
Designing an application-specific embedded system in nanometer technologies has become more difficult than ever due to the rapid increase in design complexity and manufacturing cost. Efficiency and flexibility must be carefully balanced to meet different application requirements. The recently emerged configurable and extensible processor architectures offer a favorable tradeoff between efficiency and flexibility, and a promising way to minimize certain important metrics (e.g., execution time, code size, etc.) of the embedded processors. This paper addresses the problem of generating the application-specific instructions to improve the execution speed for configurable processors. A set of algorithms, including pattern generation, pattern selection, and application mapping, are proposed to efficiently utilize the instruction set extensibility of the target configurable processor. Applications of our approach to several real-life benchmarks on the Altera Nios processor show encouraging performance speedup (2.75X on average and up to 3.73X in some cases).
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.
8796177
LIPS: Lightweight Internet Permit System for Stopping Unwanted Packets
In this paper, we propose a Lightweight Internet Permit System (LIPS) that provides a lightweight, scalable packet authentication mechanism for ensuring traffic-origin accountability. LIPS is a simple extension of IP, in which each packet carries an access permit issued by its destination host or gateway, and the destination verifies the access permit to determine if a packet is accepted or dropped. We will first present the design and the prototype implementation of LIPS on Linux 2.4 kernel. We then use analysis, simulations, and experiments to show how LIPS can effectively prevent protected critical servers and links from being flooded by unwanted packets with negligible overheads. We propose LIPS as an domain-to-domain approach to stop unwanted attacks, without requiring broad changes in backbone networks as other approaches. Therefore, LIPS is incrementally deployable in a large scale on common platforms with minor software patches.
383050
A Domain Decomposition Method for Fast Manifold Learning
We propose a fast manifold learning algorithm based on the methodology of domain decomposition. Starting with the set of sample points partitioned into two subdomains, we develop the solution of the interface problem that can glue the embeddings on the two subdomains into an embedding on the whole domain. We provide a detailed analysis to assess the errors produced by the gluing process using matrix perturbation theory. Numerical examples are given to illustrate the efficiency and effectiveness of the proposed methods.