Abstract
Image processing is widely used in intelligent robots, significantly improving the surveillance capabilities of smart buildings, industrial parks, and border ports. However, relying on the camera installed in a single robot is not enough since it only provides a narrow field of view as well as limited processing performance. Specially, a target person such as the suspect may appear anywhere and tracking the suspect in such a large-scale scene requires cooperation between fixed cameras and patrol robots. This induces a significant surge in demand for data, computing resources, as well as networking infrastructures. In this work, we develop a scalable architecture to optimize image processing efficacy and response rate for visual ability. In this architecture, the lightweight pre-process and object detection functions are deployed on the gateway-side to minimize the bandwidth consumption. Cloud-side servers receive solely the recognized data rather than entire image or video streams to identify specific suspect. Then the cloud-side sends the information to the robot, and the robot completes the corresponding tracking task. All these functions are implemented and orchestrated based on micro-service architecture to improve the flexibility. We implement a prototype system, called Rinegan, and evaluate it in an in-lab testing environment. The result shows that Rinegan is able to improve the effectiveness and efficacy of image processing.
Highlights
Image process has been widely implemented in intelligent robots, which significantly improve the visual ability of smart buildings, industrial parks, border ports and so forth
We briefly introduce the background of intelligent security robot, image processing, gateway virtualization and micro-service architecture to illustrate the motivation of our work
In order to verify that the architecture we proposed can effectively enhance the efficacy of object recognition, we implemented the protype system based on our proposed image processing architecture—Rinegan in our laboratory environment
Summary
Image process has been widely implemented in intelligent robots, which significantly improve the visual ability of smart buildings, industrial parks, border ports and so forth. Patrol robots, a critical partner of police officers or area administrators for security surveillance, are usually equipped with cameras that can track suspicious persons by collecting and processing images or video streaming. Such track task solely relying on individual and narrow view of a single robot is no longer effectiveness in large scale environment. People hope to implement a function such as face recognition on a intelligent security robot to help humans work. We briefly introduce the background of intelligent security robot, image processing, gateway virtualization and micro-service architecture to illustrate the motivation of our work
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