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IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Volpi, Michele Tuia, Devis Camps-Valls, Gustavo Kanevski, Mikhail Univ Lausanne Inst Geomat & Anal Risk CH-1015 Lausanne Switzerland Univ Valencia Image Proc Lab E-46003 Valencia Spain

ISBN: (纸本)9781457710056

In this paper we propose an unsupervised approach to change detection by computing the difference image directly in the feature spaces. The resulting difference kernel, that is a combination of kernels computed on the coregistered and radiometrically matched input images, is used to train a nonlinear partitioning algorithm. In order to apply the kernel k-means, issues related to the initialization and to the tuning of parameters (e.g. the Gaussian RBF bandwidth) are considered. To validate the proposed unsupervised algorithm, two multitemporal VHR remote sensing images are used.

关键词： Algorithm design and analysis change detection algorithms Clustering algorithms Feature extraction Kernel Partitioning algorithms Remote sensing feature extraction feature space geophysical image processing image matching image resolution kernel k-means a

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A Hierarchical, Nonparametric, Sequential change-detection Test

A Hierarchical, Nonparametric, Sequential Change-Detection T...

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International Joint Conference on Neural Networks (IJCNN)

作者： Alippi, Cesare Boracchi, Giacomo Roveri, Manuel Politecn Milan Dipartimento Elettron & Informaz I-20133 Milan Italy

ISBN: (纸本)9781424496365

Design of applications working in nonstationary environments requires the ability to detect and anticipate possible behavioral changes affecting the system under investigation. In this direction, the literature provides several tests aiming at assessing the stationarity of a data generating process;of particular interest are nonparametric sequential change-point detection tests that do not require any a-priori information regarding both process and change. Moreover, such tests can be made automatic through an on-line inspection of sequences of data, hence making them particularly interesting to address real applications. Following this approach, we suggest a novel two-level hierarchical change-detection test designed to detect possible occurrences of changes by observing incoming measurements. This hierarchical solution significantly reduces the number of false positives at the expenses of a negligible increase of false negatives and detection delays. Experiments show the effectiveness of the proposed approach both on synthetic dataset and measurements from real applications.

关键词： change detection algorithms Delay Indexes Monitoring Probability density function Process control Training data generating process data handling data sequence online inspection hierarchical change-detection test nonparametric change-detection test sequential change-detection test

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Use of an Automatic Under-Vehicle Inspection System as a Tool to Streamline Vehicle Screening at Ports of Entry and Security Checkpoints

Use of an Automatic Under-Vehicle Inspection System as a Too...

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European Intelligence and Security Informatics Conference (EISIC)

作者： Erick E. Ruiz K. Larry Head Department of Systems and Industrial Engineering University of Arizona Tucson Tucson AZ USA

Vehicle inspection at ports of entry is a critical component of border security. One part of the vehicle screening process involves customs and border protection (CBP) personnel performing a preliminary inspection of the underside of random vehicles by looking under the vehicle through a mirror mounted on a stick, searching for anomalies or foreign objects present on the undercarriage structure and components of a vehicle. If any deviances are detected, the vehicle is directed to a secondary and more thorough inspection. This paper presents a project that aims at automating this preliminary undercarriage inspection by using an automatic under-vehicle inspection system (AUVIS) and image processing algorithms to assist personnel in identifying vehicles for secondary inspection. The inspection system will image the undercarriage of every car in a lane as they approach the CBP agent and use a novel change detection algorithm to compare the captured image to a corresponding reference image of the vehicle's make and model. The software will detect and highlight any differences between the two images to provide a rapid and objective recommendation for secondary inspection.

关键词： Vehicles Inspection Cameras Image resolution Security change detection algorithms Mirrors

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Finding What changes for Two Graphs Constructed from Different Time Intervals

Finding What Changes for Two Graphs Constructed from Differe...

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IIAI International Conference on Advanced Applied Informatics (IIAIAAI)

作者： Aixiang Li Makoto Haraguchi Yoshiaki Okubo Etsuji Tomita Graduate School of Information Science Technology Hokkaido University Sapporo Japan Advanced Algorithms Research Laboratory University of Electro-Communications Chofu Tokyo Japan

Many kinds of graph data including social networks are increasing nowadays. In such a graph, the relationships between vertices are changing day by day. We need to have a data mining method able to extract significant patterns informing us about what changes. From this viewpoint, we propose in this paper an algorithm for change detection over two graphs constructed from two time intervals, based on a notion of modularity and a branch-and-bound search method for changes.

关键词： Data mining Twitter Educational institutions Correlation Joining processes Electronic mail change detection algorithms

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REAL-TIME MOTION detection BASED ON DISCRETE COSINE TRANSFORM

REAL-TIME MOTION DETECTION BASED ON DISCRETE COSINE TRANSFOR...

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IEEE International Conference on Image Processing

作者： Tae-Hyun Oh Joon-Young Lee In So Kweon Robotics and Computer Vision Laboratory KAIST South Korea

We present a motion detection algorithm by a change detection filter matrix derived from Discrete Cosine Transform. Recently, a Fourier reconstruction scheme shows good results for motion detection. However, its computational cost is a major drawback. We revisit the problem and achieve two orders of magnitude faster than the previous algorithm with better performance. The proposed algorithm runs at about 800 frames per second for VGA resolution images on a consumer hardware by using only integer matrix multiplication and the symmetric property of the change detection filter matrix. In addition, our algorithm is fundamentally robust to sudden illumination changes because it works based on edge information. We verify our algorithm with challenging datasets that contain strong and sudden illumination changes.

关键词： Discrete cosine transforms Motion detection Lighting Vectors change detection algorithms Robustness Algorithm design and analysis

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Non-parametric prediction of the mid-price dynamics in a limit order book

Non-parametric prediction of the mid-price dynamics in a lim...

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IEEE/SP Workshop on Statistical Signal Processing (SSP)

作者： Deepan Palguna Ilya Pollak School of Electrical and Computer Engineering Purdue University West Lafayette IN USA

We propose a novel non-parametric approach to short-term forecasting of the mid-price change in a limit order book (i.e., the change in the average of the best offer and the best bid prices). We construct a state vector describing the state of the order book at each time, and compute a feature vector for each value of the state vector. The features get updated during the course of a trading day, as new order flow information arrives. Our prediction at every time instant during the trading day is based on the feature vector computed at that time. The distinction of our approach from the previous ones is that it does not impose a restrictive parametric model. Implicit assumptions of our method are very mild. Initial experiments with real order book data from NYSE suggest that our algorithms show promise.

关键词： Prediction algorithms change detection algorithms Vectors Forecasting Portfolios Computer crashes Heuristic algorithms

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Lifting the Burden of History in Adaptive Ordering of Pipelined Stream Filters

Lifting the Burden of History in Adaptive Ordering of Pipeli...

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International Conference on Data Engineering Workshops

作者： Efthymia Tsamoura Anastasios Gounaris Yannis Manolopoulos Department of Informatics Aristotle University of Thessaloniki Greece

Ordering of commutative and correlated pipelined stream filters in a dynamic environment is a problem of high interest due to its application in data stream scenarios and its relevance to many query optimization problems. Current state-of-the-art adaptive techniques continuously reoptimize filter orderings utilizing statistics that are collected during the execution of the query, however, both the up-to-date and the out-of-date collected statistical data may be considered with the consequence of not always taking effective reoptimization decisions. In this work, we propose a technique for adaptive filter ordering that tries to lift the burden of out-of-date statistical data after detecting changes in the filter drop probabilities. To this end, we propose a novel drop probability change detection algorithm. The experimental evaluation shows that the proposed technique can yield significant performance improvements while decreasing the runtime overhead.

关键词： change detection algorithms Runtime detection algorithms Training Probability distribution Query processing

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A Unified Framework for Multimodal Submodular Integrated Circuits Trojan detection

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IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY 2011年第1期6卷 162-174页

作者： Koushanfar, Farinaz Mirhoseini, Azalia Rice Univ Dept Elect & Comp Engn Houston TX 77005 USA

This paper presents a unified formal framework for integrated circuits (ICs) Trojan detection that can simultaneously employ multiple noninvasive side-channel measurement types (modalities). After formally defining the IC Trojan detection for each side-channel measurement and analyzing the complexity, we devise a new submodular formulation of the problem objective function. Based on the objective function properties, an efficient Trojan detection method with strong approximation and optimality guarantees is introduced. Signal processing methods for calibrating the impact of interchip and intrachip correlations are presented. We define a new sensitivity metric that formally quantifies the impact of modifications to each existing gate that is affected by Trojan. Using the new metric, we compare the Trojan detection capability of different measurement types for static (quiescent) current, dynamic (transient) current, and timing (delay) side-channel measurements. We propose four methods for combining the detection results that are gained from different measurement modalities and show how the sensitivity results can be used for a systematic combining of the detection results. Experimental evaluations on benchmark designs reveal the low-overhead and effectiveness of the new Trojan detection framework and provides a comparison of different detection combining methods.

关键词： change detection algorithms circuit Trojan detection gate-level characterization hardware malware detection hardware security and trust submodular functions timing/power tests

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A compressed domain change detection algorithm for RTP streams in video surveillance applications

A compressed domain change detection algorithm for RTP strea...

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IEEE Workshop on Multimedia Signal Processing

作者： Marcus Laumer Peter Amon Andreas Hutter André Kaup Imaging and Visualization Siemens Corporate Technology Munich Germany Multimedia Communications and Signal Processing University of Erlangen-Nuremberg Erlangen Germany

This paper presents a novel change detection algorithm for the compressed domain. Many video surveillance systems in practical use transmit their video data over a network by using the Real-time Transport Protocol (RTP). Therefore, the presented algorithm concentrates on analyzing RTP streams to detect major changes within contained video content. The paper focuses on a reliable preselection for further analysis modules by decreasing the number of events to be investigated. The algorithm is designed to work on scenes with mainly static background, like in indoor video surveillance streams. The extracted stream elements are RTP timestamps and RTP packet sizes. Both values are directly accessible by efficient byte-reading operations without any further decoding of the video content. Hence, the proposed approach is codec-independent, while at the same time its very low complexity enables the use in extensive video surveillance systems. About 40,000 frames per second of a single RTP stream can be processed on an Intel ® Core™ 2 Duo CPU at 2 GHz and 2 GB RAM, without decreasing the efficiency of the algorithm.

关键词： Algorithm design and analysis Streaming media Transform coding Training change detection algorithms Visualization Feature extraction

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Segmentation-Based Online change detection for Mobile Robots

Segmentation-Based Online Change Detection for Mobile Robots

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2011 IEEE International Conference on Robotics and Automation(2011年IEEE世界机器人与自动化大会 ICRA 2011)

作者： Bradford Neuman Boris Sofman Anthony Stentz J. Andrew Bagnell Robotics Institute Carnegie Mellon University Pittsburgh PA 15213

The high cost of damaging an expensive robot or injuring people or equipment in its environment make even rare failures unacceptable in many mobile robot applications. Often the objects that pose the highest risk for a mobile robot are those that were not present throughout previous successful traversals of an environment. change detection, a closely related problem to novelty detection, is therefore of high importance to many mobile robotic applications that require a robot to operate repeatedly in the same environment. We present a novel algorithm for performing online change detection based on a previously developed robust online novelty detection system that uses a learned lower-dimensional representation of the feature space to perform measures of *** then further improve this change detection system by incorporating online scene segmentation to better utilize contextual information in the environment. We validate these approaches through extensive experiments onboard a large outdoor mobile robot. Our results show that our approaches are robust to noisy sensor data and moderate registration errors and maintain their performance across diverse natural environments and conditions.

关键词： Feature extraction change detection algorithms Optimization Mobile robots Mobile communication Robustness

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