207320245
Hidden Markov models with factored Gaussian mixtures densities
We present a factorial representation of Gaussian mixture models for observation densities in hidden Markov models (HMMs), which uses the factorial learning in the HMM framework. We derive the reestimation formulas for estimating the factorized parameters by the Expectation Maximization (EM) algorithm and propose a novel method for initializing them. To compare the performances of the proposed models with that of the factorial hidden Markov models and HMMs, we have carried out extensive experiments which show that this modelling approach is effective and robust.
7502395
Dynamic image sequence analysis using fuzzy measures
In this paper, we present an image understanding system using fuzzy sets and fuzzy measures. This system is based on a symbolic object-oriented image interpretation system. We apply a simple, powerful three-dimensional (3-D) recursive filter to tracking moving objects in a dynamic image sequence. This filter has a time-varying 3-D frequency-planar passband that is adapted in a feedback system to automatically track moving objects. However, as objects in the image sequence are not well-defined and are engaged in dynamic activities, their shapes and trajectories in most cases can be described only vaguely. In order to handle these uncertainties, we use fuzzy measures to capture subtle variations and manage the uncertainties involved. This enables us to develop an image understanding system that produces a very natural output. We demonstrate the effectiveness of our system with complex real traffic scenes.
4908568
Insignificant shadow detection for video segmentation
To prevent moving cast shadows from being misunderstood as part of moving objects in change detection based video segmentation, this paper proposes a novel approach to the cast shadow detection based on the edge and region information in multiple frames. First, an initial change detection mask containing moving objects and cast shadows is obtained. Then a Canny edge map is generated. After that, the shadow region is detected and removed through multiframe integration, edge matching, and region growing. Finally, a post processing procedure is used to eliminate noise and tune the boundaries of the objects. Our approach can be used for video segmentation in indoor environment. The experimental results demonstrate its good performance.
3730862
Distributed Resource Allocation in Stream Processing Systems
Distributed stream processing architecture has emerged as appealing solution to coping with the analysis of large amount of data from dispersed sources. A fundamental problem in such stream processing systems is how to best utilize the available resources so that the overall system performance is optimized. We consider a distributed stream processing system that consists of a network of cooperating servers, collectively providing processing services for multiple data streams. Each stream is required to complete a series of operations on various servers. We assume all servers have finite computing resources and all communication links have finite available bandwidth. The problem is to find distributed schemes to allocate the limited computing resources as well as the communication bandwidth in the system so as to achieve a maximum concurrent throughput for all output streams. We present a generalized multicommodity flow model for the above problem. We develop a distributed resource allocation algorithm that guarantees the optimality. We also provide detailed analysis on the complexity of the algorithm and demonstrate the performance using numerical experiments.
3756850
Clustering algorithms for content-based publication-subscription systems
We consider efficient communication schemes based on both network-supported and application-level multicast techniques for content-based publication-subscription systems. We show that the communication costs depend heavily on the network configurations, distribution of publications and subscriptions. We devise new algorithms and adapt existing partitional data clustering algorithms. These algorithms can be used to determine multicast groups with as much commonality as possible, based on the totality of subscribers' interests. They perform well in the context of highly heterogeneous subscriptions, and they also scale well. An efficiency of 60% to 80% with respect to the ideal solution can be achieved with a small number of multicast groups (less than 100 in our experiments). Some of these same concepts can be applied to match publications to subscribers in real-time, and also to determine dynamically whether to unicast, multicast or broadcast information about the events over the network to the matched subscribers. We demonstrate the quality of our algorithms via simulation experiments.
28562
Content-based indexing and retrieval-by-example in audio
This paper presents a system for audio content-based indexing and retrieval-by-example. An unsupervised method to automatically index the audio content is proposed. To realize a retrieval system where the on-line query can be performed efficiently, a new parametric distance metric is used to allow faster identification of the audio segments that are similar to the given query example. Preliminary experimental results show that the proposed new approach can serve as an effective means in content based indexing and retrieval in audio streams.
3758350
An Analytical Approach to the Performance Evaluation of Master-Slave Computational Models
Abstract Many stochastic models and analysis techniques have been proposed in the literature during the last two decades for the performance evaluation of parallel and distributed systems. However, few of them are directly applicable to practical systems which are generally too complex. In this paper, we analyze performances of the master–slave computational model, one of the most commonly used models in parallel and distributed computations. We propose a hybrid analytical approach by using techniques from the theories of both stochastic task graphs and queueing networks. We apply this method to the analysis of a computational chemistry application running on a Transputer based system. The proposed method turns out to be not only very efficient in time for large systems but also very accurate compared to measuring.