We show thye demonstration video of our research in Youtube:
https://https://youtu.be/7bw2Lof3Zv8 Using a standard video camera, it is easy to capture wide scenes of city, town, mountain, country sides as well as indoor scenes. We proposed a new algorithm for making a dense 3D image with a wide range of distance of a scene covering a wide area in a video. This kind of research target is a frontier of vision research. The obtained 3D data is suitable to use for supporting the work of robots as so-called Visual SLAM. Moreover it becomes easy to make contents of VR systems such as 3D world data for walk through. Automatic car driving becomes its application by using a video capturing a 360 degree scene by a camera on a moving car. There are many conventional methods for reconstructing a 3D image using devices such as ultrasonic, laser and infrared sensors, or techniques based on vision such as stereo vision, filling voxels method based on silhouette characteristics, object-based method, etc. However, in order to make a 3D image of a wide scene these methods still have weakness such as limit of pixel size, a small range of distance, being not applicable to non-standard reflection characteristics of the object etc. Moreover conventional methods need to combine with other techniques such as feature extraction (SIFT, etc.), factorization , RANSAC, Kalman filter etc. Therefore a new algorithm is required to overcome the weakness of conventional methods. Our method solves most of difficulties mentioned in the above. There are two kinds of 3D information for a wide scene. The one is global 3D information for distinguishing larger objects such as buildings, roads, rivers, woods, etc. The other one is for distinguishing sub- objects belonging to each larger object. Our method is applicable to extract both kinds of 3D information. Here we show only the former one. The following five images are: 1) one frame image of a video capturing city scene, 2) the RGB + distance image of 1) from a view angle. 3) a RGB +distance image constructed by video capturing our univeristy garden The part of our method was published in a paper，Ryuichi Oka and Ranaweera Rasika, Region-wise 3D Image Reconstruction from Video Based on Accumulated Moton Parallax, MIRU2017, PS1-5, August 2017. The patent of this method is now pending.