# A Regional Brightness Control Method for a Beam Projector to Avoid Human Glare
## 1 Introduction  
One of the old beam projectors developed in the 1990s, the \"Eidophor\", could project an analog video signal into a space the size of a movie theater. At the time, its effectiveness as a video output device for educational purposes was tested, and positive results were reported [1]. Thereafter, a beam projector could have been considered an effective device for implementing a large screen at a low cost.  
In recent years, beam projectors have been improving in many ways, such as in their brightness, resolution, miniaturization, and lightweight designs, thanks to advances in hardware. These improvements have led to their widespread use in education, homes, businesses, and more. Advancements in light sources are especially encouraging from the audience's perspective, as they allow for sharper images to be projected onto the screen. However, a speaker facing the beam projector may suffer from more glare due to much stronger light [2]. The intense glare can make the speaker's communication with the audience uncomfortable and even cause the speaker's vision loss from prolonged exposure. Nevertheless, the ability to present audiovisual material on a large screen for a large audience is an advantage of beam projectors, which cannot be easily achieved with other display devices. Therefore, speakers are willing to tolerate this inconvenience in many situations.  
If a beam projector could selectively adjust the area of light projection, it would prevent intense light from troubling a speaker's eyes, providing a better presentation experience while maintaining the benefits of the projector. Moreover, such a system is needed notonly by the instructors but also by the students who use projectors for their learning activities [3]. Some related research shows that beam projectors can be used to design systems that can interact with learners [4; 5]. Lin et al. proposed the basic workings of a beam projection system while considering the brightness control to protect a speaker from strong light [5]. Their research attempted to recognize faces through a camera and cover the image, illuminating the face with a black circle. To perform so, they have introduced a facial recognition algorithm based on skin color extraction to find a speaker's area over the screen.  
Nowadays, for the purpose of such human detection, a machine learning-based face recognition model [6; 7] can be a good solution. However, there are some considerations that make it difficult to directly apply typical face recognition models to the proposed system. First, the light from the beam projector is projected over the face of a speaker. This may make the recognition results quite inaccurate. Second, if an original image fed to the beam projector contains a human face, the recognition model may also detect it as a speaker. Third, if the speaker's facial area has been completely darkened due to brightness control, the recognition model will not be able to detect the face in the next stage.  
This study aims to continuously recognize human figures to find adequate areas to adjust the luminance while strong light interferes with the recognition process. For this purpose, we focus on the similarity of the images, wherein we designed a system that compares an input image of the beam projector with a captured image of the screen to find the different regions. The segmentation of the human body is performed within these different regions. In Section 3, we describe the proposed system's structure and each module's role in detail, including finding image differences, human body segmentation, and adjusting the luminance in specific areas. Section 4 presents implementation details and results by discussing some behaviors and experimental measurements.