When the same scene is captured from two different points of view, it gives an illusion of depth to the user. These two images are captured using a twin lens camera system. On the other hand, a stereo image consists of two images (left and right) representing a scene from two different points of view that are horizontally displaced. Such a system is time consuming and difficult for amateur photographers to generate 360° panoramic images. Most of the existing methods for generating mono panoramas require a lot of user input to achieve better quality results. It cannot provide depth information to the user. A mono panorama has the same view for both left and right eye. Nowadays, most of the 360° panorama contents available on the Internet are mono panorama contents. Although these embedded visual sensor-based approaches are more robust, efficient, and cost-effective for panorama generation, the quality of the panoramas generated using these embedded approaches usually suffer from stitching artifacts such as geometric error (structural error) and photometric error (color distortion).Ī massive amount of work has been done in the area of mono panorama generation where the images, captured from different angles of view with different image acquisition kits, are stitched to create a wider field of view image. Such techniques first estimate camera motion by continuous tracking of the camera while capturing images from the surroundings and stitch the images using the projected plane of the previously taken image. The third technique creates panoramas using an embedded panoramic generation system with resource-constrained devices such as mobile cameras or low-power, hand-held visual sensors. The images are then stitched together using feature-based stitching algorithms. To use this technique for panorama generation, the positioning of cameras must be set carefully with sufficient overlapping regions between adjacent cameras. The second technique generates panoramas from the images captured by multiple cameras placed in a circular rig. However, the panorama generated using this approach usually has low resolution. The first technique for panorama generation uses a single camera that projects the scene from the surroundings through a reflection in a mirror. In order to create panoramic images, there are three different techniques. Moreover, it is a suitable technique to cover wide surveillance areas such as airports, big utility stores, and banks, etc., using 360° video surveillance systems. Panoramic images have a promising future in virtual tourism, parking assistance, medical image analysis and digital cities. The generation of 360° videos requires knowledge of different fields such as image processing, computer graphics, computer vision, virtual reality, and smart city surveillance. These researchers are contributing to different aspects of 360° videos such as quality enhancement, resolution, and different image acquisition kits to capture 360° videos. Giant video and search engine servers have started to support 360° videos, thereby attracting many researchers. With the rising popularity of virtual reality, 360° panorama generation has become a hot research area. Furthermore, we compared our proposed system with existing mono and stereo contents generation systems in both qualitative and quantitative perspectives, and the comparative measurements obtained verified the effectiveness of our system compared to existing mono and stereo generation systems. We also developed stitching software that generates both mono and stereo panoramas using a single image stitching pipeline where the panorama generated by our proposed system is automatically straightened without visible seams. For stereo panorama generation, we propose a lightweight, cost-effective visual sensor kit that uses only three cameras to cover 360° of the surroundings. The hardware of our proposed image acquisition system is configured in such way that no user input is required to stitch multiple images. For mono panorama generation, we present a drone-mounted image acquisition sensor kit that consists of six cameras placed in a circular fashion with optimal overlapping gap. In this paper, we propose an economical 360° panorama generation system that generates both mono and stereo panoramas. However, these systems are equipped with expensive image sensor networks where multiple cameras are mounted in a circular rig with specific overlapping gaps. Recently, several 360° panorama generation systems have demonstrated reasonable quality generated panoramas. Also, easy access to different visual sensor kits and easily deployable image acquisition devices have played a vital role in the growth of interest in this area by the research community. In recent years, 360° videos have gained the attention of researchers due to their versatility and applications in real-world problems.
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