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检索条件"主题词=Detection and tracking algorithms"

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Hot Spot detection for Indecomposable Self-Aligned Double Patterning Layout

Hot Spot Detection for Indecomposable Self-Aligned Double Pa...

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31st International Symposium on Photomask Technology

作者： Zhang, Hongbo Du, Yuelin Wong, Martin D. F. Topaloglu, Rasit O. Univ Illinois Dept ECE Urbana IL USA GlobalFoundries Inc Milpitas CA USA

ISBN: (纸本)9780819487919

Self-aligned double patterning (SADP) lithography is a novel lithography technology which has the capability to define critical dimension (CD) using one single exposure, therefore holding a great opportunity for the next generation lithography process for the overlay mitigation. However, a necessary design manufacturing co-optimization step - the non-decomposability position detection (hot spot detection) - is still immature. In this paper, targeting the hot spot detection difficulties in SADP process, we first revisit out previous ILP-based SADP decomposition algorithm and provide an extended ILP-based hot spot detection without any preconditions on the design. Then, with some simple requirement that is commonly seen in 2D random layout, we further provided a graph based hot spot detection for an efficient hot spot detection. From the Nangate standard cell library, our experiment validates the hot spot detection process and demonstrates an SADP friendly design tyle is necessary for the upcoming 14nm technology node.

关键词： Photomasks Silicon detection and tracking algorithms Double patterning technology Lithography Manufacturing Binary data Semiconducting wafers Overlay metrology Standards development

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Stability of Recursive Out-of-Sequence Measurement Filters: An Open Problem

Stability of Recursive Out-of-Sequence Measurement Filters: ...

引用

Conference on Signal Processing, Sensor Fusion, and Target Recognition XX

作者： Chen, Lingji Moshtagh, Nima Mehra, Raman K. BAE Syst Adv Informat Technol Burlington MA 01803 USA Sci Syst Co Inc Burlington MA 01803 USA

ISBN: (纸本)9780819486240

In many applications where communication delays are present, measurements with earlier time stamps can arrive out-of-sequence, i.e., after state estimates have been obtained for the current time instant. To incorporate such an Out-Of-Sequence Measurement (OOSM), many algorithms have been proposed in the literature to obtain or approximate the optimal estimate that would have been obtained if the OOSM had arrived in-sequence. When OOSM occurs repeatedly, approximate estimations as a result of incorporating one OOSM have to serve as the basis for incorporating yet another OOSM. The question of whether the "approximation of approximation" is well behaved, i.e., whether approximation errors accumulate in a recursive setting, has not been adequately addressed in the literature. This paper draws attention to the stability question of recursive OOSM processing filters, formulates the problem in a specific setting, and presents some simulation results that suggest that such filters are indeed well-behaved. Our hope is that more research will be conducted in the future to rigorously establish stability properties of these filters.

关键词： Digital filtering Filtering (signal processing) Monte Carlo methods Time metrology Computer simulations Electronic filtering Matrices Bismuth Error analysis detection and tracking algorithms

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Real Time Topological Image Smoothing On Shared Memory Parallel Machines

Real Time Topological Image Smoothing On Shared Memory Paral...

引用

Conference on Real-Time Image and Video Processing 2011

作者： Mahmoudi, Ramzi Akil, Mohamed Univ Paris Est Cite Descartes IGM Unite Mixte CNRS UMLV ESIEE UMR8049 F-93162 Noisy Le Grand France

ISBN: (纸本)9780819484086

Smoothing filter is the method of choice for image preprocessing and pattern recognition. We present a new concurrent method for smoothing 2D object in binary case. Proposed method provides a parallel computation while preserving the topology by using homotopic transformations. We introduce an adapted parallelization strategy called split, distribute and merge (SDM) strategy which allows efficient parallelization of a large class of topological operators including, mainly, smoothing, skeletonization, and watershed algorithms. To achieve a good speedup, we cared about task scheduling. Distributed work during smoothing process is done by a variable number of threads. Tests on 2D binary image (512*512), using shared memory parallel machine (SMPM) with 8 CPU cores (2x Xeon E5405 running at frequency of 2 GHz), showed an enhancement of 5.2 thus a cadency of 32 images per second is achieved.

关键词： Image processing detection and tracking algorithms Binary data Image enhancement 3D image processing Image filtering Image segmentation Pattern recognition Linear filtering Shape analysis

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Biomimetic fusion that enhances sensor performance in a bimodal surveillance system

Biomimetic fusion that enhances sensor performance in a bimo...

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Conference on Unattended Ground, Sea, and Air Sensor Technologies and Applications XIII

作者： Ziph-Schatzberg, Leah Kelsall, Sarah Hubbard, Allyn E. Boston Univ Photon Ctr 8 St Marys St Boston MA 02215 USA Elect Boat Corp Groton CT 06340 USA Boston Univ Dept Elect & Comp Engn Boston MA USA

ISBN: (纸本)9780819486202

algorithms for synergistically fusing acoustic and optical sensory inputs, thereby mimicking biological attentional processes are described. Manual existing perimeter defense surveillance systems using more than one sensory modality combine different sensors' information to corroborate findings by other sensors and to add data from a second modality. In contrast to how conventional systems work, animals use information from multiple sensory inputs in a way that improves each sensory system's performance. We demonstrated that performance is enhanced when information in one modality is used to focus processing in the other modality (a form of attention). This synergistic bi-modal operation improves surveillance efficacy by focusing auditory and visual "attention" on a particular target or location. algorithms for focusing auditory and visual sensors using detection information were developed. These combination algorithms perform "zoom-with-enhanced-acuity" in both the visual and auditory domains, triggered by detection in either domain. Sensory-input processing algorithms focus on specific locations, indicated by at least one of the modalities. This spatially focused processing emulates biological attention-driven focusing. We showed that given information about the target, the acoustic algorithms were able to achieve over 80% correct target detection at signal-to-noise ratios (SNRs) of -20 dB and above, as compared with similar performance at SNRs of -10 db and above without target information from another modality. Similarly, the visual algorithm achieved performance of over 80% detection with added noise variance of 0.001 without target indication, but maintained 100% detection at added noise variance of 0.05 when acoustic target information was taken into account.

关键词： detection and tracking algorithms Target detection Sensors Video Visualization Algorithm development Signal to noise ratio Cameras Acoustics Visual system

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Optimal exposure sets for High Dynamic Range Scenes

Optimal exposure sets for High Dynamic Range Scenes

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International Conference on Graphic and Image Processing (ICGIP)

作者： Kumari, V. Valli RaviKiran, B. Raju, K. V. S. V. N. Basha, S. A. Shajahan Andhra Univ Visakhapatnam Andhra Pradesh India Anil Neerukonda Inst Technol Visakhapatnam Andhra Pradesh India

ISBN: (纸本)9780819489326

The dynamic range of many natural scenes is far greater than the dynamic range of the imaging devices. These scenes present a challenge to the consumer digital cameras. The well-known technique to capture the full dynamic range of the scene is by fusing multiple images of the same scene. Usually people combine three or five different exposures to get the full dynamic range of the scene. Some cameras like Pentax K-7, always combines fixed exposures together to produce the output result. However, this should be adaptive to the scene characteristics. We propose an optimal solution for dynamically selecting the exposure sets.

关键词： High dynamic range imaging Light sources and illumination Cameras Imaging devices Digital cameras detection and tracking algorithms Eye Sensors Visual system Image processing

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Detector Defect Correction of Medical Images on Graphics Processors

Detector Defect Correction of Medical Images on Graphics Pro...

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Conference on Medical Imaging 2011 - Image Processing

作者： Membarth, Richard Hannig, Frank Teich, Juergen Litz, Gerhard Hornegger, Heinz Univ Erlangen Nurnberg Dept Comp Sci Erlangen Germany Siemens Healthcare Sector HIMAX Forchheim Germany

ISBN: (纸本)9780819485045

The ever increasing complexity and power dissipation of computer architectures in the last decade blazed the trail for more power efficient parallel architectures. Hence, such architectures like field-programmable gate arrays (FPGAs) and particular graphics cards attained great interest and are consequently adopted for parallel execution of many number crunching loop programs from fields like image processing or linear algebra. However, there is little effort to deploy barely computational, but memory intensive applications to graphics hardware. This paper considers a memory intensive detector defect correction pipeline for medical imaging with strict latency requirements. The image pipeline compensates for different effects caused by the detector during exposure of X-ray images and calculates parameters to control the subsequent dosage. So far, dedicated hardware setups with special processors like DSPs were used for such critical processing. We show that this is today feasible with commodity graphics hardware. Using CUDA as programming model, it is demonstrated that the detector defect correction pipeline consisting of more than ten algorithms is significantly accelerated and that a speedup of 20 x can be achieved on NVIDIA's Quadro FX 5800 compared to our reference implementation. For deployment in a streaming application with steadily new incoming data, it is shown that the memory transfer overhead of successive images to the graphics card memory is reduced by 83% using double buffering.

关键词： Visualization Sensors Image processing Medical imaging detection and tracking algorithms Digital signal processing Imaging systems X-rays Computer architecture X-ray detectors

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A MRF Model with Parameter Optimization by CRF for On-line Recognition of Handwritten Japanese Characters

A MRF Model with Parameter Optimization by CRF for On-line R...

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Conference on Document Recognition and Retrieval XVIII

作者： Zhu, Bilan Nakagawa, Masaki Tokyo Univ Agr & Technol Dept Comp Sci Tokyo 1848588 Japan

ISBN: (纸本)9780819484116

This paper describes a Markov random field (MRF) model with weighting parameters optimized by conditional random field (CRF) for on-line recognition of handwritten Japanese characters. The model extracts feature points along the pen-tip trace from pen-down to pen-up and sets each feature point from an input pattern as a site and each state from a character class as a label. It employs the coordinates of feature points as unary features and the differences in coordinates between the neighboring feature points as binary features. The weighting parameters are estimated by CRF or the minimum classification error (MCE) method. In experiments using the TUAT Kuchibue database, the method achieved a character recognition rate of 92.77%, which is higher than the previous model's rate, and the method of estimating the weighting parameters using CRF was more accurate than using MCE.

关键词： Magnetorheological finishing Binary data Optical character recognition Databases detection and tracking algorithms Feature extraction Optimization (mathematics) Error analysis Performance modeling Prototyping

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A Multiple Feature Based Particle Filter Using Mutual Information Maximization

A Multiple Feature Based Particle Filter Using Mutual Inform...

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Conference on Intelligent Robots and Computer Vision XXVIII: algorithms and Techniques

作者： Hong, Kihyun Han, Kyuseo Purdue Univ W Lafayette IN 47907 USA

ISBN: (纸本)9780819484154

In designing a tracking algorithm, utilizing several different features, e. g., color histogram, gradient histogram and other object descriptors, is preferable to increase robustness of tracking performance. In this paper, we propose a multiple feature fusion framework to improve the tracking by assigning appropriate weights to individual features. The feature weights are optimally obtained by a waterfilling procedure that maximizes mutual information between target object features and query features. Especially, in this paper, we focus on a particle filter tracking implementation of the multiple feature fusion framework. Our experiments show that object tracking with multiple features outperforms single feature based tracking methods and illustrates that the proposed optimal feature weighting increases robustness of multiple-feature based tracking performance.

关键词： Particle filters detection and tracking algorithms Particles Process modeling Algorithm development Signal to noise ratio Visual process modeling Computer vision technology Dynamical systems Machine vision

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Efficient object tracking in WAAS data streams

Efficient object tracking in WAAS data streams

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Conference on Real-Time Image and Video Processing 2011

作者： Clarke, Trevor R. H. Canosa, Roxanne Ball Aerosp & Technol Corp Boulder CO 80301 USA Rochester Inst Technol Rochester NY 14623 USA

ISBN: (纸本)9780819484086

Wide area airborne surveillance (WAAS) systems are a new class of remote sensing imagers which have many military and civilian applications. These systems are characterized by long loiter times (extended imaging time over fixed target areas) and large footprint target areas. These characteristics complicate moving object detection and tracking due to the large image size and high number of moving objects. This research evaluates existing object detection and tracking algorithms with WAAS data and provides enhancements to the processing chain which decrease processing time and maintain or increase tracking accuracy. Decreases in processing time are needed to perform real-time or near real-time tracking either on the WAAS sensor platform or in ground station processing centers. Increased tracking accuracy benefits real-time users and forensic (off-line) users.

关键词： Cameras Imaging systems Sensors detection and tracking algorithms Video Algorithm development Image processing Optical flow Unmanned aerial vehicles Video surveillance

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View Morphing using Linear Prediction of Sub-Space Features

View Morphing using Linear Prediction of Sub-Space Features

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Conference on Automatic Target Recognition XXI

作者： Mahalanobis, Abhijit Berkowitz, Phil Shah, Mubarak Lockheed Martin Missiles & Fire Control Orlando FL 32819 USA Univ Cent Florida Dept Phys Orlando FL 32826 USA

ISBN: (纸本)9780819486233

We present a mathematical technique for estimating new perspective views of an object from a single image. Unlike traditional graphics or ray tracing methods, our approach treats the view-morphing problem as a 2-D linear prediction process. We first estimate the prediction parameters in a reduced dimensional space using features extracted from "training" images of the object. Given an arbitrary view of the object, the features of the new view are linearly predicted from which the morphed image of the object is reconstructed. The proposed approach can be used for rapidly incorporating new objects in the knowledge base of a computer vision system and may have advantages in low-contrast situations where it is difficult to establish correspondence between sample views.

关键词： Image filtering Image sensors Image processing Sensors detection and tracking algorithms Infrared imaging Visualization Computing systems Feature extraction Thermography

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