1651955
Feature Matching under Region-Based Constraints for Robust Epipolar Geometry Estimation
Outlier-free inter-frame feature matches are important to accurate epipolar geometry estimation for many vision and robotics applications. We discover a set of high-level geometric and appearance constraints on low-level feature matches by exploiting reliable region matching results. A new outlier filtering scheme based on these constraints is proposed that can be combined with traditional robust statistical methods to identify outlier feature matches more reliably and efficiently. The proposed filtering scheme is tested in an real application of outdoor mobile robot navigation based on far-field scenes and of scenes that contain repeated structures.
7928906
Augmenting Exercise Systems with Virtual Exercise Environment
Adhering to an exercise program is a challenge for everybody who wants to build a healthier body and lifestyle through physical exercise. We have developed an Virtual Exercise Environment (VEE) that augments stationary exercise equipment with virtual reality techniques to make exercising more enjoyable. Our VEE system consists of a recording system to capture video, distance and incline data about real trails, and a playback system which "displays" both video and terrain data in the form of video speed and resistance. Trails are played back according to the speed the user generates on the stationary exercise equipment. The system uses commodity capture and display devices and supports standard interfaces for existing exercise equipment. User studies have shown that users enjoy the ability to guage their progress and performance via their progress through trail playback in the VEE.
38303932
Fuzzy inference based on fuzzy concept lattice
In this paper, a fuzzy inference method based on the notion of fuzzy concept lattice is studied. We first propose a new form of fuzzy concept lattice, and then based on three kinds of known fuzzy concept lattices and our new fuzzy concept lattice, two coherent fuzzy inference methods, the lower approximate fuzzy inference and the upper approximate fuzzy inference, are proposed, and the combined use of the two methods will make the fuzzy inference more precise.
9180515
Incremental Spectral Clustering With Application to Monitoring of Evolving Blog Communities
In recent years, spectral clustering method has gained attentions because of its superior performance compared to other traditional clustering algorithms such as K-means algorithm. The existing spectral clustering algorithms are all off-line algorithms, i.e., they can not incrementally update the clustering result given a small change of the data set. However, the capability of incrementally updating is essential to some applications such as real time monitoring of the evolving communities of websphere or blogsphere. Unlike traditional stream data, these applications require incremental algorithms to handle not only insertion/deletion of data points but also similarity changes between existing items. This paper extends the standard spectral clustering to such evolving data by introducing the incidence vector/matrix to represent two kinds of dynamics in the same framework and by incrementally updating the eigenvalue system. Our incremental algorithm, initialized by a standard spectral clustering, continuously and efficiently updates the eigenvalue system and generates instant cluster labels, as the data set is evolving. The algorithm is applied to a blog data set. Compared with recomputation of the solution by standard spectral clustering, it achieves similar accuracy but with much lower computational cost. Close inspection into the blog content shows that the incremental approach can discover not only the stable blog communities but also the evolution of the individual multi-topic blogs.
850350
Online System Problem Detection by Mining Patterns of Console Logs
We describe a novel application of using data mining and statistical learning methods to automatically monitor and detect abnormal execution traces from console logs in an online setting. Different from existing solutions, we use a two stage detection system. The first stage uses frequent pattern mining and distribution estimation techniques to capture the dominant patterns (both frequent sequences and time duration). The second stage use principal component analysis based anomaly detection technique to identify actual problems. Using real system data from a 203-node Hadoop [1] cluster, we show that we can not only achieve highly accurate and fast problem detection, but also help operators better understand execution patterns in their system.
30164221
Limited feedback design for MIMO broadcast channels with ARQ mechanism
We investigate the design of a limited feedback mechanism for multiple-input-multiple-output (MIMO) broadcast systems that are equipped with automatic repeat request (ARQ) capabilities. Given multiple antennas at the base-station (BS) and single antenna subscribers, we focus on maximizing the ergodic system sum capacity and propose an adaptive feedback bit allocation scheme under the constraint of total feedback bandwidth. Furthermore, we develop two efficient feedback allocation schemes based on asymptotic analysis. We present simulation results that verify the effectiveness of the proposed adaptive allocation schemes.
29524091
Adaptive complete synchronization of the noise-perturbed two bi-directionally coupled chaotic systems with time-delay and unknown parametric mismatch
In this paper, we design an adaptive-feedback controller to synchronize a class of noise-perturbed two bi-directionally coupled chaotic systems with time-delay and unknown parametric mismatch. Based on invariance principle of stochastic time-delay differential equations, some sufficient conditions of adaptive complete synchronization are given. Comparing with other papers, here we consider the effect of internal noise, time-delay and parametric mismatch in the synchronized process. As the illustrative examples, the famous Lorenz system and Rossler system are considered here. In order to validate the proposed scheme, numerical simulations are performed, and the numerical results show that our scheme is very effective.