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A Closed-Form Expression for Thin Lens image Irradiance 7

A Closed-Form Expression for Thin Lens Image Irradiance

引用

7th International conference on image processing Theory, Tools and applications (IPTA)

作者： Friedlander, Robert D. Yezzi, Anthony J. Georgia Inst Technol Sch Elect & Comp Engn Atlanta GA 30332 USA

ISBN: (纸本)9781538618424

Computer vision tasks often have the goal of inferring geometric and radiometric information about a 3D environment given limited sensing resources. It is helpful to develop relationships between these real-world properties and the actual measurements that are taken. To this end we propose a new relationship between object radiance and image irradiance based on power conservation and a thin lens imaging model. The relationship has a closed-form solution for in-focus points and can be solved via numerical integration for points that are not focused. It can be thought of as a generalization of Horn's irradiance equation. Through both numerical simulations and comparison with the intensity values of actual images, our equation is shown to provide better accuracy than Horn's equation. Improvement is most notable for near-focused images where the pinhole imaging model implicit in Horn's derivation breaks down. Outside of this regime, our model validates the use of Horn's approximation.

关键词： Computer vision image formation Pinhole camera model Radiometry Photometry Thin lens model

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Design and FPGA Implementation of Residual Data in HEVC CABAC Encoder

Design and FPGA Implementation of Residual Data in HEVC CABA...

引用

International conference on signal, image, Vision and their applications (SIVA )

作者： Menasri Wahiba Skoudarli Abdellah Mohamed Salah Azzaz Belhadj Aichouche USTHB-Faculty of Electronic and Informatic Laboratory of Image Processing and Radiation BP 32 El Alia Bab Ezzouar Algiers Algeria École Militaire Polytechnique Laboratoire Systèmes Électroniques et Numériques BP 17 Bordj El-Bahri Algiers Algeria

ISBN: (纸本)9781538671214;9781538671207

Context-based Adaptive Binary Arithmetic Coding (CABAC) is an efficient entropy codec, adopted by H.264/AVC (advanced video codec) and H.265/HEVC (High Efficiency Video Coding) standards. HEVC is the newest standard of video compression, it is expected to achieve at a least 4K and 8K ultra-HD resolution up to 120 fps. CABAC is already a well-known bottleneck in H.265. In this paper, we propose a new RTL (Register Transfer Level) architecture of HEVC CABAC encoder, where all Syntax Elements (SE) transmitted for 4 x 4 sub-block are studied and implemented. This architecture is described using structural hardware description VHDL language. To achieve a good compromise in terms of path-delay, speed and hardware resources some optimization techniques are adopted. Our implementation of the HEVC CABAC encoder processed for 1.2 bins/cycle needs only 478 of slices with a maximum frequency of 134.885 MHz and high throughput of 161.86 Mbin/s. Simulation and hardware implementation on xilinx FPGA technology results demonstrates that the proposed architecture provides a good compromise in terms of resources and throughput.

关键词： Encoding Context modeling Hardware Standards Throughput Transforms Video coding

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Correlation-based 2D Registration Method for Single Particle Cryo-EM images 7

Correlation-based 2D Registration Method for Single Particle...

引用

7th International conference on image processing Theory, Tools and applications (IPTA)

作者： Anoshina, Nadezhda A. Krylov, Andrey S. Sorokin, Dmitry V. Lomonosov Moscow State Univ Fac Computat Math & Cybernet Lab Math Methods Image Proc Moscow Russia Masaryk Univ Fac Informat Ctr Biomed Image Anal Brno Czech Republic

ISBN: (纸本)9781538618424

The amount of image data generated in single particle cryo-electron microscopy (cryo-EM) is huge. This technique is based on the reconstruction of the 3D model of a particle using its 2D projections. The most common way to reduce the noise in particle projection images is averaging. The essential step before the averaging is the alignment of projections. In this work, we propose a fast 2D rigid registration approach for alignment of particle projections in single particle cryo-EM. We used cross-correlation in Fourier domain combined with polar transform to find the rotation angle invariant to the shift between the images. For translation vector estimation we used a fast version of upsampled image correlation. Our approach was evaluated on specifically created synthetic dataset. An experimental comparison with a widely used in existing software iterative method has been performed. In addition, it was successfully applied to a real dataset from the Electron Microscopy Data Bank (EMDB).

关键词： image registration cryo-electron microscopy cryo-EM particle alignment

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Comparing Keyframe Summaries of Egocentric Videos: Closest-to-Centroid Baseline 7

Comparing Keyframe Summaries of Egocentric Videos: Closest-t...

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7th International conference on image processing Theory, Tools and applications (IPTA)

作者： Kuncheva, Ludmila I. Yousefi, Paria Almeida, Jurandy Bangor Univ Sch Comp Sci Bangor Gwynedd Wales Univ Fed Sao Paulo UNIFESP Inst Ciencia & Tecnol Sao Paulo Brazil

ISBN: (纸本)9781538618424

Evaluation of keyframe video summaries is a notoriously difficult problem. So far, there is no consensus on guidelines, protocols, benchmarks and baseline models. This study contributes in three ways: (1) We propose a new baseline model for creating a keyframe summary, called Closest-to-Centroid, and show that it is a better contestant compared to the two most popular baselines: uniform sampling and choosing the mid-event frame. (2) We also propose a method for matching the visual appearance of keyframes, suitable for comparing summaries of egocentric videos and lifelogging photostreams. (3) We examine 24 image feature spaces (different descriptors) including colour, texture, shape, motion and a feature space extracted by a pre trained convolutional neural network (CNN). Our results using the four egocentric videos in the UTE database favour low-level shape and colour feature spaces for use with CC.

关键词： Video summarisation Keyframe selection Egocentric video image feature descriptors Closest-to-Centroid baseline model Keyframe evaluation protocol

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Low Cost Target Design and Detection for Camera Calibration in image Based Close Range Inspection applications

Low Cost Target Design and Detection for Camera Calibration ...

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International conference on Vision, image and signal processing ICVISP

作者： Heinemann, David Baumgarten, Daniel Knabner, Steffen Tech Univ Ilmenau Inst Biomed Engn & Informat Multimodal Data Anal Grp Ilmenau Germany Ingenieurburo Steffen Knabner Magdala Germany

ISBN: (纸本)9781538606124

Camera calibration is a widely covered and well-known topic, which has been discussed and well described in many publications. However, the detection of the corresponding calibration markers can be problematic if the imaging setup considers a very short working distance, a huge magnification and special lighting setups, which is the case in almost every industrial inspection system, especially in surface inspection. Low-cost calibration targets can have poor quality in terms of surface homogeneity, resulting in reflection and illumination artifacts. In this paper, we present a distance transform based approach for detecting calibration markers of those targets. As an example application, the typical setup of a surface inspection system for printed circuit boards is used. This approach ensures a built-in calibration process without the need of changing the imaging setup.

关键词： camera calibration close range application inspection system calibration target distance transform marker detection

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Vehicle Re-identification by Fusing Multiple Deep Neural Networks 7

Vehicle Re-identification by Fusing Multiple Deep Neural Net...

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7th International conference on image processing Theory, Tools and applications (IPTA)

作者： Cui, Chao Sang, Nong Gao, Changxin Zou, Lei Huazhong Univ Sci & Technol Minist Educ Image Proc & Intelligent Control Key Lab Wuhan Hubei Peoples R China

ISBN: (纸本)9781538618424

Vehicle re-identification has become a fundamental task because of the growing explosion in the use of surveillance cameras in public security. The most widely used solution is based on license plate verification. But when facing the vehicle without a license, deck cars and other license plate information error or missing situation, vehicle searching is still a challenging problem. This paper proposed a vehicle re-identification method based on deep learning which exploit a two-branch Multi-DNN Fusion Siamese Neural Network (MFSNN) to fuses the classification outputs of color, model and pasted marks on the windshield and map them into a Euclidean space where distance can be directly used to measure the similarity of arbitrary two vehicles. In order to achieve this goal, we present a method of vehicle color identification based on Alex net, a method of vehicle model identification based on VGG net, a method of pasted marks detection and identification based on Faster R-CNN. We evaluate our MFSNN method on VehiclelD dataset and in the experiment. Experiment results show that our method can achieve promising results.

关键词： Vehicle re-identification MFSNN Alex net VGG net Faster-RCNN

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Pixelwise Classification for Music Document Analysis 7

Pixelwise Classification for Music Document Analysis

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7th International conference on image processing Theory, Tools and applications (IPTA)

作者： Calvo-Zaragoza, Jorge Vigliensoni, Gabriel Fujinaga, Ichiro McGill Univ Schulich Sch Mus Ctr Interdisciplinary Res Mus Media & Technol Montreal PQ Canada

ISBN: (纸本)9781538618424

Content within musical documents not only contains music symbol but also include different elements such as staff lines, text, or frontispieces. Before attempting to automatically recognize components in these layers, it is necessary to perform an analysis of the musical documents in order to detect and classify each of these constituent parts. The obstacle for this analysis is the high heterogeneity amongst music collections, especially with ancient documents, which makes it difficult to devise methods that can be generalizable to a broader range of sources. In this paper we propose a data-driven document analysis framework based on machine learning that focuses on classifying regions of interest at pixel level. For that, we make use of Convolutional Neural Networks trained to infer the category of each pixel. The main advantage of this approach is that it can be applied regardless of the type of document provided, as long as training data is available. Since this work represents first efforts in that direction, our experimentation focuses on reporting a baseline classification using our framework. The experiments show promising performance, achieving an accuracy around 90% in two corpora of old music documents.

关键词： Document image Analysis Optical Music Recognition Music Archives Pixel classification Convolutional Neural Network

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Fast perceptual image hash based on cascade algorithm 40

Fast perceptual image hash based on cascade algorithm

引用

conference on applications of Digital image processing xL

作者： Ruchay, Alexey Kober, Vitaly Yavtushenko, Evgeniya Chelyabinsk State Univ Dept Math Chelyabinsk Russia CICESE Dept Comp Sci Carretera Ensenada Tijuana 3918 Ensenada 22860 Baja California Mexico Chelyabinsk State Univ Dept Phys Chelyabinsk Russia

ISBN: (数字)9781510612501

ISBN: (纸本)9781510612501;9781510612495

In this paper, we propose a perceptual image hash algorithm based on cascade algorithm, which can be applied in image authentication, retrieval, and indexing. image perceptual hash uses for image retrieval in sense of human perception against distortions caused by compression, noise, common signal processing and geometrical modifications. The main disadvantage of perceptual hash is high time expenses. In the proposed cascade algorithm of image retrieval initializes with short hashes, and then a full hash is applied to the processed results. Computer simulation results show that the proposed hash algorithm yields a good performance in terms of robustness, discriminability, and time expenses.

关键词： perceptual hash fast hash image hash

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High-speed, low-complexity video coding with EDiCTius: A DCT coding proposal for JPEG xS 40

High-speed, low-complexity video coding with EDiCTius: A DCT...

引用

conference on applications of Digital image processing xL

作者： Richter, Thomas Foessel, Siegfried Keinert, Joachim Scherl, Christian Univ Stuttgart TIK Comp Ctr IZUS D-70550 Stuttgart Germany Fraunhofer Inst Integrated Circuits IIS D-91058 Erlangen Germany

ISBN: (数字)9781510612501

ISBN: (纸本)9781510612501;9781510612495

In its 71th meeting, the JPEG committee issued a call for low complexity, high speed image coding, designed to address the needs of low-cost video-over-ip applications. As an answer to this call, Fraunhofer IIS and the Computing Center of the University of Stuttgart jointly developed an embedded DCT image codec requiring only minimal resources while maximizing throughput on FPGA and GPU implementations. Objective and subjective tests performed for the 73(rd) meeting confirmed its excellent performance and suitability for its purpose, and it was selected as one of the two key contributions for the development of a joined test model. In this paper, its authors describe the design principles of the codec, provide a high-level overview of the encoder and decoder chain and provide evaluation results on the test corpus selected by the JPEG committee.

关键词： Digital signal processing image compression Video coding Computer programming Field programmable gate arrays image processing image transmission Performance modeling Video Video acceleration

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ExAMPLE-BASED VISUAL OBJECT COUNTING FOR COMPLEx BACKGROUND WITH A LOCAL LOW-RANK CONSTRAINT

EXAMPLE-BASED VISUAL OBJECT COUNTING FOR COMPLEX BACKGROUND ...

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IEEE International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Huang, x. L. Zou, Y. x. Wang, Y. Peking Univ Sch ECE ADSPLAB ELIP Shenzhen 518055 Peoples R China

ISBN: (纸本)9781509041176

Visual object counting (VOC) is important in many real-world applications. Our previous work approximated sparsity-constrain example-based VOC (ASE-VOC) works well with insufficient training data. It assumes that image patches share the similar local geometry with counterpart density maps, and then the density map of the image patch can be estimated by preserving such geometry. However, ASE-VOC has a weak constraint for data structure and experiments reveal that the performance of ASE-VOC degrades when facing with complex background. To solve this problem, we proposed a novel local low-rank constrained example-based VOC (LLRE-VOC) method. Because local low-rank constraint can choose the samples belonging to the subspace that lies closest to the test samples. Even with complicated data structure, LLRE-VOC can guarantee the patches selected share similar structure with input patch. Extensive experiments conducted on public benchmarks demonstrate the superior performance of our proposed LLRE-VOC method.

关键词： Visual object counting complex background local low-rank density map estimation example-based

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