scholarly journals Literature Survey on Stereo Vision Disparity Map Algorithms

2016 ◽  
Vol 2016 ◽  
pp. 1-23 ◽  
Author(s):  
Rostam Affendi Hamzah ◽  
Haidi Ibrahim
Keyword(s):  
Stereo Vision ◽  
Stereo Matching ◽  
Literature Survey ◽  
Processing Unit ◽  
Stereo Correspondence ◽  
Disparity Map ◽  
Central Processing ◽  
Field Programmable ◽  
Processing Module ◽  
Graphical Processing

This paper presents a literature survey on existing disparity map algorithms. It focuses on four main stages of processing as proposed by Scharstein and Szeliski in a taxonomy and evaluation of dense two-frame stereo correspondence algorithms performed in 2002. To assist future researchers in developing their own stereo matching algorithms, a summary of the existing algorithms developed for every stage of processing is also provided. The survey also notes the implementation of previous software-based and hardware-based algorithms. Generally, the main processing module for a software-based implementation uses only a central processing unit. By contrast, a hardware-based implementation requires one or more additional processors for its processing module, such as graphical processing unit or a field programmable gate array. This literature survey also presents a method of qualitative measurement that is widely used by researchers in the area of stereo vision disparity mappings.

scholarly journals Implementación de redes neuronales en FPGAs usando tipos de datos de punto fijo

2020 ◽  
Vol 8 ◽  
Author(s):  
Daniel Enériz Orta ◽  
Nicolás Medrano Marqués ◽  
Belén Calvo López
Keyword(s):  
Field Programmable Gate Array ◽  
A Priori ◽  
Central Processing Unit ◽  
Processing Unit ◽  
Central Processing ◽  
Field Programmable ◽  
Gate Array

La capacidad de estimar funciones no lineales hace que las redes neuronales sean una de las herramientas más usadas para aplicar fusión sensorial, permitiendo combinar la salida de diferentes sensores para obtener información de la que a priori no se dispone. Por otra parte, la capacidad de procesamiento paralelo de las FPGAs (Field-Programmable Gate Array) las hace idóneas para implementar redes neuronales ubicuas, permitiendo inferir resultados más rápido que una CPU (Central Processing Unit) sin necesidad de una conexión activa a internet. De esta forma, en este artículo se propone un flujo de trabajo para diseñar, entrenar e implementar una red neuronal en una FPGA Xilinx PYNQ Z2 que use tipos de dato de punto fijo para hacer fusión sensorial. Dicho flujo de trabajo es probado mediante el desarrollo de una red neuronal que combine las salidas de una nariz artificial de 16 sensores para obtener una estimación de las concentraciones de CH4 y C2H4.

scholarly journals Real-Time Monte Carlo Optimization on FPGA for the Efficient and Reliable Message Chain Structure

Electronics ◽  
2019 ◽  
Vol 8 (8) ◽  
pp. 866 ◽  
Author(s):  
Heoncheol Lee ◽  
Kipyo Kim
Keyword(s):  
Monte Carlo ◽  
Real Time ◽  
Communication Systems ◽  
Optimization Method ◽  
Chain Structure ◽  
Processing Unit ◽  
Monte Carlo Optimization ◽  
Central Processing ◽  
Field Programmable ◽  
Programmable Gate Arrays

This paper addresses the real-time optimization problem to find the most efficient and reliable message chain structure in data communications based on half-duplex command–response protocols such as MIL-STD-1553B communication systems. This paper proposes a real-time Monte Carlo optimization method implemented on field programmable gate arrays (FPGA) which can not only be conducted very quickly but also avoid the conflicts with other tasks on a central processing unit (CPU). Evaluation results showed that the proposed method can consistently find the optimal message chain structure within a quite small and deterministic time, which was much faster than the conventional Monte Carlo optimization method on a CPU.

Experimental validation of a virtual engine-out NOx sensor for diesel emission control

2019 ◽  
Vol 20 (10) ◽  
pp. 1037-1046 ◽  
Author(s):  
Paul Mentink ◽  
Daniel Escobar-Valdivieso ◽  
Alexandru Forrai ◽  
Xander Seykens ◽  
Frank Willems
Keyword(s):  
Processing Unit ◽  
Central Processing ◽  
Nox Sensor ◽  
Heavy Duty Diesel Engine ◽  
Field Programmable ◽  
Diesel Emission ◽  
Diesel Emission Control ◽  
Heavy Duty Diesel ◽  
Main Input ◽  
Automotive Emission

Motivated by automotive emission legislations, a Virtual [Formula: see text] sensor is developed. This virtual sensor consists of a real-time, phenomenological model that computes engine-out [Formula: see text] by using the measured in-cylinder pressure signal from a single cylinder as its main input. The implementation is made on a Field Programmable Gate Array–Central Processing Unit architecture to ensure the [Formula: see text] computation is ready at the end of the combustion cycle. The Virtual [Formula: see text] sensor is tested and validated on an EURO-VI Heavy-Duty Diesel engine platform. The Virtual [Formula: see text] sensor is proven to meet the accuracy of a production [Formula: see text] sensor for steady-state conditions and has better frequency response compared to the production [Formula: see text] sensor.

scholarly journals LTTng CLUST: A System-Wide Unified CPU and GPU Tracing Tool for OpenCL Applications

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
David Couturier ◽  
Michel R. Dagenais
Keyword(s):  
Application Programming Interface ◽  
Third Party ◽  
Battery Life ◽  
Portable Devices ◽  
Processing Unit ◽  
Central Processing ◽  
Application Programming ◽  
Graphical Processing ◽  
Performance Analysis Tools ◽  
Programming Interface

As computation schemes evolve and many new tools become available to programmers to enhance the performance of their applications, many programmers started to look towards highly parallel platforms such as Graphical Processing Unit (GPU). Offloading computations that can take advantage of the architecture of the GPU is a technique that has proven fruitful in recent years. This technology enhances the speed and responsiveness of applications. Also, as a side effect, it reduces the power requirements for those applications and therefore extends portable devices battery life and helps computing clusters to run more power efficiently. Many performance analysis tools such as LTTng, strace and SystemTap already allow Central Processing Unit (CPU) tracing and help programmers to use CPU resources more efficiently. On the GPU side, different tools such as Nvidia’s Nsight, AMD’s CodeXL, and third party TAU and VampirTrace allow tracing Application Programming Interface (API) calls and OpenCL kernel execution. These tools are useful but are completely separate, and none of them allow a unified CPU-GPU tracing experience. We propose an extension to the existing scalable and highly efficient LTTng tracing platform to allow unified tracing of GPU along with CPU’s full tracing capabilities.

Image Stereo Correspondence Method for Stereo Vision

2013 ◽  
Vol 475-476 ◽  
pp. 337-341
Author(s):  
Ai Hua Chen ◽  
Cheng Hui Gao ◽  
Bing Wei He
Keyword(s):  
3D Reconstruction ◽  
Stereo Vision ◽  
Stereo Matching ◽  
Target Recognition ◽  
Future Research ◽  
Stereo Correspondence ◽  
Research Issues ◽  
Vision Measurement ◽  
The Core ◽  
Core Technology

Image stereo correspondence is the core technology of stereo vision. It has been widely studied and applied in the fields such as 3D reconstruction, vision measurement and target recognition. According to characteristics and application of stereo matching technology, the image stereo correspondence methods can be classified into three categories: local stereo correspondence, global stereo correspondence and semi-global stereo correspondence. Some image stereo correspondence solutions and problems are emphatically analyzed. Finally some future research issues on image stereo correspondence are highlighted.

Real time area-based stereo matching algorithm for multimedia video devices

2013 ◽  
Vol 21 (4) ◽  
Author(s):  
T. Hachaj ◽  
M. Ogiela
Keyword(s):  
Real Time ◽  
Stereo Matching ◽  
Global Memory ◽  
Stereo Pair ◽  
Processing Unit ◽  
Process Data ◽  
Matching Algorithm ◽  
Knowing That ◽  
Algorithm Configuration ◽  
Graphical Processing

AbstractIn this paper we investigate stereovision algorithms that are suitable for multimedia video devices. The main novel contribution of this article is detailed analysis of modern graphical processing unit (GPU)-based dense local stereovision matching algorithm for real time multimedia applications. We considered two GPU-based implementations and one CPU implementation (as the baseline). The results (in terms of frame per second, fps) were measured twenty times per algorithm configuration and, then averaged (the standard deviation was below 5%). The disparity range was [0,20], [0,40], [0,60], [0,80], [0,100] and [0,120]. We also have used three different matching window sizes (3×3, 5×5 and 7×7) and three stereo pair image resolutions 320×240, 640×480 and 1024×768. We developed our algorithm under assumption that it should process data with the same speed as it arrives from captures’ devices. Because most popular of the shelf video cameras (multimedia video devices) capture data with the frequency of 30Hz, this frequency was threshold to consider implementation of our algorithm to be “real time”. We have proved that our GPU algorithm that uses only global memory can be used successfully in that kind of tasks. It is very important because that kind of implementation is more hardware-independent than algorithms that operate on shared memory. Knowing that we might avoid the algorithms failure while moving the multimedia application between machines operating different hardware. From our knowledge this type of research has not been yet reported.

scholarly journals Method for improving ripple reduction during phase shedding in multiphase buck converters for SCADA systems

2021 ◽  
Vol 24 (1) ◽  
pp. 29
Author(s):  
Mini P. Varghese ◽  
A. Manjunatha ◽  
T. V. Snehaprabha
Keyword(s):  
Power Supply ◽  
Integrated Circuit ◽  
Buck Converter ◽  
Multiphase System ◽  
Processing Unit ◽  
Central Processing ◽  
Light Load ◽  
Field Programmable ◽  
Ripple Reduction ◽  
Application Specific Integrated Circuit

In the current digital environment, central processing unit (CPUs), field programmable gate array (FPGAs), application-specific integrated circuit (ASICs), as well as peripherals, are growing progressively complex. On motherboards in many areas of computing, from laptops and tablets to servers and Ethernet switches, multiphase phase buck regulators are seen to be more common nowadays, because of the higher power requirements. This study describes a four-stage buck converter with a phase shedding scheme that can be used to power processors in programmable logic controller (PLCs). The proposed power supply is designed to generate a regulated voltage with minimal ripple. Because of the suggested phase shedding method, this power supply also offers better light load efficiency. For this objective, a multiphase system with phase shedding is modeled in MATLAB SIMULINK, and the findings are validated.

scholarly journals Implementation of Stereo Vision Semi-Global Block Matching Methods for Distance Measurement

2018 ◽  
Vol 12 (2) ◽  
pp. 585 ◽  
Author(s):  
Raden Arief Setyawan ◽  
Rudy Sunoko ◽  
Mochammad Agus Choiron ◽  
Panca Mudji Rahardjo
Keyword(s):  
Stereo Vision ◽  
Stereo Matching ◽  
Distance Estimation ◽  
Distance Measurement ◽  
Block Matching ◽  
Disparity Map ◽  
Block Matching Algorithm ◽  
Object Distance ◽  
Left And Right ◽  
3D Movie

Stereo vision has become an attractive topic research in the last decades. Many implementations such as the autonomous car, 3D movie, 3D object generation, are produced using this technique. The advantages of using two cameras in stereo vision are the disparity map between images. Disparity map will produce distance estimation of the object. Distance measurement is a crucial parameter for an autonomous car. The distance between corresponding points between the left and right images must be precisely measured to get an accurate distance. One of the most challenging in stereo vision is to find corresponding points between left and right images (stereo matching). This paper proposed distance measurement using stereo vision using Semi-Global Block Matching algorithm for stereo matching purpose. The object is captured using a calibrated stereo camera. The images pair then optimized using WLS Filter to reduce noises. The implementation results of this algorithm are furthermore converted to a metric unit for distance measurement. The result shows that the stereo vision distance measurement using Semi-Global Block Matching gives a good result. The obtained best result of this work contains error of less than 1% for 1m distance

scholarly journals GPU Accelerated real-time Melanoma Detection

2018 ◽  
Vol 7 (3) ◽  
pp. 1208
Author(s):  
Ajai Sunny Joseph ◽  
Elizabeth Isaac
Keyword(s):  
Real Time ◽  
Video Processing ◽  
Processing Technique ◽  
Video Data ◽  
Image Processing Technique ◽  
Processing Unit ◽  
Central Processing ◽  
Melanoma Detection ◽  
Real Time Analysis ◽  
Graphical Processing

Melanoma is recognized as one of the most dangerous type of skin cancer. A novel method to detect melanoma in real time with the help of Graphical Processing Unit (GPU) is proposed. Existing systems can process medical images and perform a diagnosis based on Image Processing technique and Artificial Intelligence. They are also able to perform video processing with the help of large hardware resources at the backend. This incurs significantly higher costs and space and are complex by both software and hardware. Graphical Processing Units have high processing capabilities compared to a Central Processing Unit of a system. Various approaches were used for implementing real time detection of Melanoma. The results and analysis based on various approaches and the best approach based on our study is discussed in this work. A performance analysis for the approaches on the basis of CPU and GPU environment is also discussed. The proposed system will perform real-time analysis of live medical video data and performs diagnosis. The system when implemented yielded an accuracy of 90.133% which is comparable to existing systems.  

scholarly journals New Stereo Vision Algorithm Composition Using Weighted Adaptive Histogram Equalization and Gamma Correction

2021 ◽  
Vol 15 (3) ◽  
pp. 239-250
Author(s):  
Ahmad Fauzan Kadmin ◽  
Rostam Affendi ◽  
Nurulfajar Abd. Manap ◽  
Mohd Saad ◽  
Nadzrie Nadzrie ◽  
...  
Keyword(s):  
Stereo Vision ◽  
Vision System ◽  
Median Filter ◽  
Histogram Equalization ◽  
Gamma Correction ◽  
Stereo Correspondence ◽  
Disparity Map ◽  
Depth Measurement ◽  
Adaptive Histogram Equalization ◽  
Processing Step

This work presents the composition of a new algorithm for a stereo vision system to acquire accurate depth measurement from stereo correspondence. Stereo correspondence produced by matching is commonly affected by image noise such as illumination variation, blurry boundaries, and radiometric differences. The proposed algorithm introduces a pre-processing step based on the combination of Contrast Limited Adaptive Histogram Equalization (CLAHE) and Adaptive Gamma Correction Weighted Distribution (AGCWD) with a guided filter (GF). The cost value of the pre-processing step is determined in the matching cost step using the census transform (CT), which is followed by aggregation using the fixed-window and GF technique. A winner-takes-all (WTA) approach is employed to select the minimum disparity map value and final refinement using left-right consistency checking (LR) along with a weighted median filter (WMF) to remove outliers. The algorithm improved the accuracy 31.65% for all pixel errors and 23.35% for pixel errors in nonoccluded regions compared to several established algorithms on a Middlebury dataset.

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