# Supervised Learning Based Peripheral Vision System for
## 1 Introduction  
The television (TV) is considered as one of the major sources of the living room entertainment with the huge improvement in the visual and audio quality of the display over the past few years. However, the TV display has two limitations [1].  
1. It only provides the screen with the limited content and field of view as the peripheral vision system lacks due to the limited screen size and the image formats.
2. It provides the visual experience restricted to the virtual scene boxed in the frame of the display and the physical environment surrounding the user is neglected.  
The solution to these problems is the automatic generation of the new content beyond the existing screen size and image formats, and their projection onto the periphery of TV screen using projector [2]. This augmentation leads to immersive, interactive, and entertaining visual experiences for the user. Though the user may manually create the plausible content for the existing TV screen, it is too expensive to create it.  
Peripheral projection is an efficient technique to enhance the visual experiences of the user, but its employment is limited in the common display applications due to the difficult problem of the context image generation [3]. Context (or context image) refers to the image or Video frame projected on the wall around the traditional TV screen to create immersive experiences [3]. Illumiroom [1] explained the concept of the context including the full image content, edges, partial image content and other special effects to enhance the visual experiences of the user. The proposed work utilized the F + C Full context [1] as the context image (see Table 1). The problem of context image generation was solved bythe approaches either based on computer vision algorithm or deep neural network in the literature [3; 4; 5; 6].  
In this paper, we propose the peripheral vision system that has the capability to produce immersive display projecting the content extended by deep neural network around the TV screen. The goals of the system are as follows:  
1. The design of the system to augment the area surrounding the TV with projected context image creating immersive visual experiences.
2. Replacing the traditional video display with the immersive visual experiences for the user at low cost using the components of the TV and projector easily available everywhere.
3. Quantitative and qualitative evaluation of our system with the State of the Art approaches The proposed system is expected to pave a new road to the home appliance industry by transforming the living room into the new immersive experience platform. The proposed research provides immersive visual experiences to the user relaxing in living room and finds applications in gaming and for broadcasting video.  
This paper is organized as follows: Section 2 presents a comparative overview of the existing related research work. Section 3 provides the brief overview of the proposed system and the methodology to extend the video content using deep neural network. Section 4 presents the experiments and results for the context-image generation and extended display application. Section 5 includes the conclusion and future research.