veilscreen80's profile
Location: Ashkāsham, Jowzjan, Hong Kong S.A.R.
Member: July 18, 2022
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Last active: July 18, 2022
Description: We present a novel synthetic dataset MinNav based on the sandbox game Minecraft. This dataset uses several plug-in program to generate rendered image sequences with time-aligned depth maps, surface normal maps and camera poses. MinNav is a highly scalable dataset, users not only can easily obtain a large number of big-scale 3d scene files in the community, saving modeling time, but also can build specific scenes in the game. what’s more, thanks for its open source feature, users can also develop modules to obtain other ground-truth for different purpose in research. Different from other synthetic datasets, our proposed dataset has a community of a large number of players, which can build 3d scenes and obtain tools at a lower cost, and because there are a large number of light and shadow rendering tools, the generated synthetic dataset can be greatly reduced Distribution deviation from real-world data.Understanding scenes through video is a significant research in visual perception. It includes many classical computer vision tasks, such as depth recovery, surface normal prediction and visual odometry etc. Undoubtedly, data sets are the top priority of research.Presently datasets[7, 4] has already been applied in industrial such as autonomous driving [3], interactive collaborative robotics [5], and localization and navigation systems [6], etc . But Kirn -truth of these always suffer the approximately measurement limited by the sensor, or even unavailable, requiring huge cost. Most synthetic dataset[2, 10] based on open-source film makes up for the above shortcomings partly. It also provide a new opportunity for computer vision research. What’s more ,the data bias between synthetic data and real-world data is unavoidable problem and limited amount of data, especially the scene, is Gradually unable to meet demand of resent model.We propose a simply method to generate high quality synthetic dataset based on open-source game Minecraft includes rendered image, Depth map, surface normal map, and 6-dof camera trajectory. This dataset has a perfect ground-truth generated by plug-in program, and thanks for the large game’s community, there is an extremely large number of 3D open-world environment, users can find suitable scenes for shooting and build data sets through it and they can also build scenes in-game. as such, We don’t need to worry about manual over fitting caused by too small datasets. what’s more, there is also a shader community which We can use to minimize data bias between rendered images and real-images as little as possible. Last but not least, we now provide three tools to generate the data for depth prediction ,surface normal prediction and visual odometry, user can also develop the plug-in module for other vision task like segmentation or optical flow prediction.2 Preparatory toolsIt is a sandbox video game created by Swedish game developer Markus Persson and released by Mojang in 2011. The game allows players to build with a variety of different blocks in a 3D procedurally generated world, and has already been a tools in several research[9, 1, 11]. It minimum component is block sized 1×1×11111\times 1\times 11 × 1 × 1, and map loading range is a square with 1536×1536153615361536\times 15361536 × 1536 , support player to redevelop plug-in module to achieve specific function.Replay Modis a Modification for the Minecraft which allows players to record and replay their gaming experience with monocular, stereo, or even 360D videos. Player can generate dynamic 3d scene file centered as main player and set camera trajectories manually with adjustable fov.The 3d scene file support rendered by Blender, and also could be rendered in real-time by third-party shader.Optifineis a Minecraft optimization mod. It allows Minecraft to run faster and look better with full support for HD textures and many configuration options. We have developed two shader3 thought it to generate precise ground-truth in sync with image sequences.SildurSildur is an open-source shader written in GLSL, it adds shadows, dynamic lighting, and waving grass, leaves and water to increase the reality , reduce the data bias between rendered data and real-data.3 Generation of DatasetsIn this paper, we choose a big game map AudiaCity 2.0 (Fig. 4) as scene to build MinNav.It contains over 1,500 buildings , covering an area of 16 square kilometers and an altitude of 67 meters. including schools, hospitals, libraries,wharves and factories etc, has a good diversity to meet most demand111https://www.planetminecraft.com/project/audia-project-minecraft-city/. \dirtree.1 MinNav. .2 Games -number.png. .5 …. .4 depth. .5 frame-number.png. .5 …. .4 timestamp.txt. .4 camera-state.txt. \dirtree.1 Grids Raw Files. .2 grid-number. .3 SceneNumber.mcpr. .3 timelines.json. .3 …. .2 ….It obviously that the map can not loaded into limited memory all at once, We sampling every 400 meters in both directions divided the whole map into several Grids sized as a 800m×800800
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