OpenVX is increasingly gaining consensus as standard platform to develop portable, optimized and power-efficient embedded vision applications. Nevertheless, adopting OpenVX for rapid prototyping, early algorithm parametrization and validation of complex embedded applications is a very challenging task. This paper presents a comprehensive framework that integrates Simulink, OpenVX, and ROS for model-based design of embedded vision applications. The framework allows applying Matlab-Simulink for the model-based design, parametrization, and validation of computer vision applications. Then, it allows for the automatic synthesis of the application model into an OpenVX description for the hardware and constraints-aware application tuning. Finally, the methodology allows integrating the OpenVX application with Robot Operating System (ROS), which is the de-facto reference standard for developing robotic software applications. The OpenVX-ROS interface allows co-simulating and parametrizing the application by considering the actual robotic environment and the application reuse in any ROS-compliant system. Experimental results have been conducted with two real case studies: An application for digital image stabilization and the ORB descriptor for simultaneous localization and mapping (SLAM), which have been developed through Simulink and, then, automatically synthesized into OpenVX-VisionWorks code for an NVIDIA Jetson TX2 board

Integrating Simulink, OpenVX, and ROS for Model-Based Design of Embedded Vision Applications

Stefano Aldegheri;Nicola Bombieri
2019

Abstract

OpenVX is increasingly gaining consensus as standard platform to develop portable, optimized and power-efficient embedded vision applications. Nevertheless, adopting OpenVX for rapid prototyping, early algorithm parametrization and validation of complex embedded applications is a very challenging task. This paper presents a comprehensive framework that integrates Simulink, OpenVX, and ROS for model-based design of embedded vision applications. The framework allows applying Matlab-Simulink for the model-based design, parametrization, and validation of computer vision applications. Then, it allows for the automatic synthesis of the application model into an OpenVX description for the hardware and constraints-aware application tuning. Finally, the methodology allows integrating the OpenVX application with Robot Operating System (ROS), which is the de-facto reference standard for developing robotic software applications. The OpenVX-ROS interface allows co-simulating and parametrizing the application by considering the actual robotic environment and the application reuse in any ROS-compliant system. Experimental results have been conducted with two real case studies: An application for digital image stabilization and the ORB descriptor for simultaneous localization and mapping (SLAM), which have been developed through Simulink and, then, automatically synthesized into OpenVX-VisionWorks code for an NVIDIA Jetson TX2 board
EMBEDDED VISION
Model-based Design
OpenVX
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/1001134
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