15384375
A hybrid source-channel coding scheme for object-based wireless video communications
In this paper, we study the joint source-channel coding of object-based video, and propose a data hiding scheme that improves the video error resilience by adaptively embedding the shape and motion information in the texture data. Within a rate-distortion theoretical framework, the source coding, channel coding, data embedding, and decoder error concealment are jointly optimized based on the knowledge of transmission channel conditions. The problem is solved using Lagrangian relaxation and dynamic programming. Experimental results indicate that the proposed hybrid source-channel coding scheme significantly outperforms methods without data hiding or unequal error protection
14473430
An optimal shape encoding scheme using skeleton decomposition
This paper presents an operational rate-distortion (ORD) optimal approach for skeleton-based boundary encoding. The boundary information is first decomposed into skeleton and distance signals, by which a more efficient representation of the original boundary results. Curves of arbitrary order are utilized for approximating the skeleton and distance signals. For a given bit budget for a video frame, we solve the problem of choosing the number and location of the control points for all skeleton and distance signals and for all boundaries within a frame, so that the overall distortion is minimized. The problem is solved with the use of Lagrangian relaxation and a shortest path algorithm in a 4D directed acyclic graph (DAG) we propose. By defining a path selection pattern, we reduce the computational complexity of the 4D DAG shortest path algorithm from O(N/sup -5/) to O(N/sup -4/), where N is the number of admissible control points for a skeleton. A suboptimal solution is also presented for further reducing the computational complexity of the algorithm to O(N/sup -2/). The proposed algorithm outperforms experimentally other competing algorithms.
7895439
An efficient rate-distortion optimal shape coding approach utilizing a skeleton-based decomposition
In this paper, we present a new shape-coding approach, which decouples the shape information into two independent signal data sets; the skeleton and the boundary distance from the skeleton. The major benefit of this approach is that it allows for a more flexible tradeoff between approximation error and bit budget. Curves of arbitrary order can be utilized for approximating both the skeleton and distance signals. For a given bit budget for a video frame, we solve the problem of choosing the number and location of the control points for all skeleton and distance signals of all boundaries within a frame, so that the overall distortion is minimized. An operational rate-distortion (ORD) optimal approach using Lagrangian relaxation and a four-dimensional direct acyclic graph (DAG) shortest path algorithm is developed for solving the problem. To reduce the computational complexity from O(N(5)) to O(N(3)), where N is the number of admissible control points for a skeleton, a suboptimal greedy-trellis search algorithm is proposed and compared with the optimal algorithm. In addition, an even more efficient algorithm with computational complexity O(N(2)) that finds an ORD optimal solution using a relaxed distortion criterion is also proposed and compared with the optimal solution. Experimental results demonstrate that our proposed approaches outperform existing ORD optimal approaches, which do not follow the same decomposition of the source data.
11673267
Object-based video compression scheme with optimal bit allocation among shape, motion and texture
In object-based video, the encoding of the video data is decoupled into the encoding of shape, motion and texture information, which enables certain functionalities like content-based interactivity and scalability. However, the problem of how to jointly encode these separate signals to reach the best coding efficiency has never been solved thoroughly. In this paper, we present an operational rate-distortion optimal bit allocation scheme that provides a solution to this problem. Our approach is based on the Lagrangian relaxation and dynamic programming. Experimental results indicate that the proposed optimal encoding approach has considerable gains over an ad-hoc method without optimization. Furthermore the proposed algorithm is much more efficient than exhaustive search.
15118493
Anomaly intrusion detection using multi-objective genetic fuzzy system and agent-based evolutionary computation framework
In this paper, we present a multi-objective genetic fuzzy system for anomaly intrusion detection. The proposed system extracts accurate and interpret able fuzzy rule-based knowledge from network data using an agent-based evolutionary computation framework. The experimental results on KDD-Cup99 intrusion detection benchmark data demonstrate that our system can achieve high detection rate for intrusion attacks and low false positive rate for normal network traffic.
7308728
Fluent speech prosody: Framework and modeling
Abstract The prosody of fluent connected speech is much more complicated than concatenating individual sentence intonations into strings. We analyzed speech corpora of read Mandarin Chinese discourses from a top–down perspective on perceived units and boundaries, and consistently identified speech paragraphs of multiple phrases that reflected discourse rather than sentence effects in fluent speech. Subsequent cross-speaker and cross-speaking-rate acoustic analyses of identified speech paragraphs revealed systematic cross-phrase prosodic patterns in every acoustic parameter, namely, F0 contours, duration adjustment, intensity patterns, and in addition, boundary breaks. We therefore argue for a higher prosodic node that governs, constrains, and groups phrases to derive speech paragraphs. A hierarchical multi-phrase framework is constructed to account for the governing effect, with complimentary production and perceptual evidences. We show how cross-phrase F0 and syllable duration patterns templates are derived to account for the tune and rhythm characteristic to fluent speech prosody, and argue for a prosody framework that specifies phrasal intonations as subjacent sister constituent subject to higher terms. Output fluent speech prosody is thus cumulative results of contributions from every prosodic layer. To test our framework, we further construct a modular prosody model of multiple-phrase grouping with four corresponding acoustic modules and begin testing the model with speech synthesis. To conclude, we argue that any prosody framework of fluent speech should include prosodic contributions above individual sentences in production, with considerations of its perceptual effects to on-line processing; and development of unlimited TTS could benefit most appreciably by capturing and including cross-phrase relationships in prosody modeling.
6373946
A data stream language and system designed for power and extensibility
By providing an integrated and optimized support for user-defined aggregates (UDAs), data stream management systems (DSMS) can achieve superior power and generality while preserving compatibility with current SQL standards. This is demonstrated by the Stream Mill system that, through is Expressive Stream Language (ESL), efficiently supports a wide range of applications - including very advanced ones such as data stream mining, streaming XML processing, time-series queries, and RFID event processing. ESL supports physical and logical windows (with optional slides and tumbles) on both built-in aggregates and UDAs, using a simple framework that applies uniformly to both aggregate functions written in an external procedural languages and those natively written in ESL. The constructs introduced in ESL extend the power and generality of DSMS, and are conducive to UDA-specific optimization and efficient execution as demonstrated by several experiments.
10547222
A Hybrid Ontology Directed Feedback Selection Algorithm for Supporting Creative Problem Solving Dialogues
We evaluate a new hybrid language processing approach designed for interactive applications that maintain an interaction with users over multiple turns. Specifically, we describe a method for using a simple topic hierarchy in combination with a standard information retrieval measure of semantic similarity to reason about the selection of appropriate feedback in response to extended language inputs in the context of an interactive tutorial system designed to support creative problem solving. Our evaluation demonstrates the value of using a machine learning approach that takes feedback from experts into account for optimizing the hierarchy based feedback selection strategy.
6238577
Labeling Scheme and Structural Joins for Graph-Structured XML Data
When XML documents are modeled as graphs, many challenging research issues arise. In particular, query processing for graph-structured XML data brings new challenges because traditional structural join methods cannot be directly applied. In this paper, we propose a labeling scheme for graph-structured XML data. With this labeling scheme, the reachability relationship of two nodes can be judged efficiently without accessing other nodes. Based on this labeling scheme, we design efficient structural join algorithms to evaluate reachability queries. Experiments show that our algorithms have high efficiency and good scalability.