Neuronal Specialization for Fine-Grained Distance Estimation Using a Real-Time Bio-Inspired Stereo Vision System

Human vision is a complex system which involves processing frames and retrieving information in a real-time with optimization of the memory, energy and computational resources usage. It can be widely utilized in many real-world applications from security systems to space missions. The research investigates fundamental principles of human vision and accordingly develops a FPGA-based video processing system with binocular vision, capable of high performance and real-time tracking of moving objects in 3D space. The undertaken research and implementation consist of: 1. Analysis of concepts and methods of human vision system; 2. Development stereo and peripheral vision prototype of a system-on-programmable chip (SoPC) for multi-object motion detection and tracking; 3. Verification, test run and analysis of the experimental results gained on the prototype and associated with the performance constraints; The implemented system proposes a platform for real-time applications which are limited in current approaches.

Enhanced Manufacturing Execution System “MES” Through a Smart Vision System

Lecture Notes in Mechanical Engineering - Advances on Mechanics, Design Engineering and Manufacturing III ◽

10.1007/978-3-030-70566-4_52 ◽

2021 ◽

pp. 329-334

Author(s):

Chawki El Zant ◽

Quentin Charrier ◽

Khaled Benfriha ◽

Patrick Le Men

Keyword(s):

Control Systems ◽

Real Time ◽

Visual Inspection ◽

Vision System ◽

Processing System ◽

Inspection System ◽

Manufacturing Execution System ◽

Novel Approach ◽

Industrial Performance ◽

Security Operations

AbstractThe level of industrial performance is a vital issue for any company wishing to develop and acquire more market share. This article presents a novel approach to integrate intelligent visual inspection into “MES” control systems in order to gain performance. The idea is to adapt an intelligent image processing system via in-situ cameras to monitor the production system. The images are thus analyzed in real time via machine learning interpreting the visualized scene and interacting with some features of the MES system, such as maintenance, quality control, security, operations, etc. This novel technological brick, combined with the flexibility of production, contributes to optimizing the system in terms of autonomy and responsiveness to detect anomalies, already encountered, or even new ones. This smart visual inspection system is considered as a Cyber Physical System CPS brick integrated to the manufacturing system which will be considered an edge computing node in the final architecture of the platform. This smart CPS represents the 1st level of calculation and analysis in real time due to embedded intelligence. Cloud computing will be a perspective for us, which will represent the 2nd level of computation, in deferred time, in order to analyze the new anomalies encountered and identify potential solutions to integrate into MES. Ultimately, this approach strengthens the robustness of the control systems and increases the overall performance of industrial production.

Object distance estimation algorithm for real-time FPGA-based stereoscopic vision system

High-Performance Computing in Geoscience and Remote Sensing VIII ◽

10.1117/12.2324851 ◽

2018 ◽

Author(s):

Simon E. Korepanov ◽

Sergey A. Smirnov ◽

Valery V. Strotov ◽

Alexey V. Cherpalkin

Keyword(s):

Real Time ◽

Vision System ◽

Distance Estimation ◽

Estimation Algorithm ◽

Stereoscopic Vision ◽

Object Distance

Kinect in neurorehabilitation: Computer vision system for real time hand and object detection and distance estimation

11th Symposium on Neural Network Applications in Electrical Engineering ◽

10.1109/neurel.2012.6419983 ◽

2012 ◽

Cited By ~ 5

Author(s):

Matija Strbac ◽

Marko Markovic ◽

Dejan B. Popovic

Keyword(s):

Computer Vision ◽

Object Detection ◽

Real Time ◽

Vision System ◽

Distance Estimation ◽

Computer Vision System

FPGA-Based Stereo-Vision System Mimicking Human Binocular Vision

10.32920/ryerson.14646192.v1 ◽

2021 ◽

Author(s):

Gvarami Labartkava

Keyword(s):

Real Time ◽

Binocular Vision ◽

Video Processing ◽

High Performance ◽

Moving Objects ◽

Peripheral Vision ◽

Vision System ◽

Processing System ◽

Object Motion ◽

Human Vision

Human vision is a complex system which involves processing frames and retrieving information in a real-time with optimization of the memory, energy and computational resources usage. It can be widely utilized in many real-world applications from security systems to space missions. The research investigates fundamental principles of human vision and accordingly develops a FPGA-based video processing system with binocular vision, capable of high performance and real-time tracking of moving objects in 3D space. The undertaken research and implementation consist of: 1. Analysis of concepts and methods of human vision system; 2. Development stereo and peripheral vision prototype of a system-on-programmable chip (SoPC) for multi-object motion detection and tracking; 3. Verification, test run and analysis of the experimental results gained on the prototype and associated with the performance constraints; The implemented system proposes a platform for real-time applications which are limited in current approaches.

REAL TIME VIDEO STITCHING IMPLEMENTATION ON A ZYNQ FPGA SOC

10.32920/ryerson.14654502 ◽

2021 ◽

Author(s):

Dhimiter Qendri

Keyword(s):

Real Time ◽

Imaging System ◽

Vision System ◽

Processing System ◽

Video Stream ◽

Panoramic Imaging ◽

Vision Processing ◽

Video Stitching ◽

Panoramic Video ◽

Set Up

This project details the design and implementation of an image processing pipeline that targets real time video-stitching for semi-panoramic video synthesis. The scope of the project includes the analysis of possible approaches, selection of processing algorithms and procedures, design of experimental hardware set-up (including the schematic capture design of a custom catadioptric panoramic imaging system) and firmware/software development of the vision processing system components. The goal of the project is to develop a frame-stitching IP module as well as an efficient video registration algorithm capable for synthesis of a semi-panoramic video-stream at 30 frames-per-second (fps) rate with minimal FPGA resource utilization. The developed components have been validated in hardware. Finally, a number of hybrid architectures that make use of the synergy between the CPU and FPGA section of the ZYNQ SoC have been investigated and prototyped as alternatives to a complete hardware solution. Keyword: Video stitching, Panoramic vision, FPGA, SoC, vision system, registration

Omni-Vision System of Intelligent Car Based on DSP & FPGA

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.187.109 ◽

2012 ◽

Vol 187 ◽

pp. 109-114

Author(s):

Yu Bin Zhou ◽

Yu Ning Yang

Keyword(s):

Real Time ◽

Vision System ◽

Processing System ◽

Data Sampling ◽

Time Data ◽

Digital Videos ◽

Real Time Processing ◽

High Data ◽

2D Data ◽

Data Transferring

In order to realize omni-vision system of intelligent car for auto wandering in real-time processing, an image processing system with 6 vision channels based on FPGA&DSP is designed. In the system, two ZBT SRAM chips are used as the input and output cache for high data transferring. A FPGA chip is responsible for the core logic controlling and video synchronous. Digital videos are sent so processing module by camlink bus. Data are exchanged by EMIF and McBSP between FPGA and DSPs. EDMA is used for data transferring between SRAM in FPGA and ZBT SRAM. The QDMA is used for 2D data transferring to 1D into DSP cache. Tasks are assigned to chips by μC/OS on master DSP. All this together, real-time data sampling and processing for multi-channel vision was realized.

REAL TIME VIDEO STITCHING IMPLEMENTATION ON A ZYNQ FPGA SOC

10.32920/ryerson.14654502.v1 ◽

2021 ◽

Author(s):

Dhimiter Qendri

Keyword(s):

Real Time ◽

Imaging System ◽

Vision System ◽

Processing System ◽

Video Stream ◽

Panoramic Imaging ◽

Vision Processing ◽

Video Stitching ◽

Panoramic Video ◽

Set Up

This project details the design and implementation of an image processing pipeline that targets real time video-stitching for semi-panoramic video synthesis. The scope of the project includes the analysis of possible approaches, selection of processing algorithms and procedures, design of experimental hardware set-up (including the schematic capture design of a custom catadioptric panoramic imaging system) and firmware/software development of the vision processing system components. The goal of the project is to develop a frame-stitching IP module as well as an efficient video registration algorithm capable for synthesis of a semi-panoramic video-stream at 30 frames-per-second (fps) rate with minimal FPGA resource utilization. The developed components have been validated in hardware. Finally, a number of hybrid architectures that make use of the synergy between the CPU and FPGA section of the ZYNQ SoC have been investigated and prototyped as alternatives to a complete hardware solution. Keyword: Video stitching, Panoramic vision, FPGA, SoC, vision system, registration

A real-time processing system for determination of metabolic rates of a suited astronaut

10.2514/6.1969-993 ◽

1969 ◽

Author(s):

D. BILLINGSLEY ◽

G. HUMBERT ◽

R. KELLY

Keyword(s):

Real Time ◽

Processing System ◽

Metabolic Rates ◽

Real Time Processing ◽

Time Processing

Network Selection in Wireless Heterogeneous Environment Based on Available Bandwidth Estimation

Recent Patents on Computer Science ◽

10.2174/2213275912666191018112959 ◽

2019 ◽

Vol 12 ◽

Author(s):

Kiran Ahuja ◽

Brahmjit Singh ◽

Rajesh Khanna

Keyword(s):

Real Time ◽

Estimation Error ◽

Network Selection ◽

Bandwidth Estimation ◽

Heterogeneous Environment ◽

Bootstrap Approximation ◽

Available Bandwidth ◽

Internet Connection ◽

Available Bandwidth Estimation ◽

Selection Of

Background: With the availability of multiple options in wireless network simultaneously, Always Best Connected (ABC) requires dynamic selection of the best network and access technologies. Objective: In this paper, a novel dynamic access network selection algorithm based on the real time is proposed. The available bandwidth (ABW) of each network is required to be estimated to solve the network selection problem. Method: Proposed algorithm estimates available bandwidth by taking averages, peaks, low points and bootstrap approximation for network selection. It monitors real-time internet connection and resolves the selection issue in internet connection. The proposed algorithm is capable of adapting to prevailing network conditions in heterogeneous environment of 2G, 3G and WLAN networks without user intervention. It is implemented in temporal and spatial domains to check its robustness. Estimation error, overhead, estimation time with the varying size of traffic and reliability are used as the performance metrics. Results: Through numerical results, it is shown that the proposed algorithm’s ABW estimation based on bootstrap approximation gives improved performance in terms of estimation error (less than 20%), overhead (varies from 0.03% to 83%) and reliability (approx. 99%) with respect to existing techniques. Conclusion: Our proposed methodology of network selection criterion estimates the available bandwidth by taking averages, peaks, and low points and bootstrap approximation method (standard deviation) for the selection of network in the wireless heterogeneous environment. It monitors real-time internet connection and resolves internet connections selection issue. All the real-time usage and test results demonstrate the productivity and adequacy of available bandwidth estimation with bootstrap approximation as a practical solution for consistent correspondence among heterogeneous wireless networks by precise network selection for multimedia services.