## 1 Introduction  
Image and video processing [1; 2] have made it possible to create solutions that promote the surveillance of people in need of assistance [3; 4; 5]. In recent times, progress has been made in home monitoring using small unmanned aerial vehicles (UAVs). However, incorporating autonomous flying vehicles requires excessively costly and hazardous testing in real environments. For this reason, some proposals are directed towards simulation using virtual and augmented environments [6; 7; 8], allowing scaled prototyping, evaluation and testing at a much lower cost and with no physical risk to people. Our research group is working in this line, developing a virtual reality (VR) simulation platform for small UAVs as future social robots for monitoring dependent people in the home [9; 10]. One should note that any VR platform intended to evaluate the performance of robots prior to the live experience must operate with real-time accuracy. Any such platform also allows one to tailor the design to the preferences of potential end users, so virtual environments and simulations must be as realistic as possible, which certainly can be computationally expensive [11]. Unity is one of the most widely used graphics engines for creating virtual simulators. This Unity game engine is widely used for simulation projects and for quickly generating 3D environments [12]. Therefore, the proposed platform uses Unity to recreate home environments where a virtual UAV monitors a dependent person's avatar, simulating the behaviour of the future aerial assistant. The operation of the UAV will rely heavily on visual information processing. Using the onboard camera as the main sensor, the aerial robot would know where the person is for the monitoring process, determining his or her status and assistance needs [13]. It would also detect and avoid obstacles in the flight path to ensure safe operation. The VR platform will be paramount to programming the computer vision algorithms and evaluating their performance in a safe environment before the physical assistance UAV advances to the next design stage. Therefore, this work aims to study the video-processing capabilities in Unity, even though this engine was originally developed to create and develop video games, and not for image processing. Currently there are several solutions to this interoperability problem, such as client-server architectures, subscribe/publish communication [14] or the development of native libraries for use without the need to adapt external communication [15]. Although they are only usable in the operating systems they were developed for, native plugins allow the generation of functionalities that cannot be realised in the C# language or through the Unity framework. In this paper, we considered it appropriate to evaluate two approaches to video processing from Unity using OpenCV (Open Source Computer Vision Library), which are summarised as follows. (1) Using a DLL programmed in C++, and (2) programming an external module in Python that communicates through MQTT with the main program. The way of implementing video processing using OpenCV may affect the final performance of the simulator, so it is important to compare and determine the best option to avoid technical problems such as delays and bottlenecks derived from data transmission and/or processing. Therefore, the main contribution of this work is to compare and evaluate the two approaches. The remainder of this paper is structured as follows. Section 2 introduces some related works. Section 3 presents an overview of the study conducted concerning the integration of OpenCV in Unity and illustrates the two compared approaches, a native C++ DLL and an external Python module communicated via MQTT. It also details the hardware and software used, discusses the main differences between both approaches and describes how images are converted and transferred from Unity.