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      "body": "YEs Iam surely intrested in 3d printing ..planned to buy one earlier but It got dropped somehow ..Would love to see your 3d creations thou . . Welcome to the family  .. would love to read more posts by you .. keep posting\nUpvoted the post!\nYou Can follow me @utfull if you like\nWill follow you back! See you around.",
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      "body": "wow that's awesome stuff\nkeep going, take my upvote ^^ and steem on\ngonna follow you to see with what you'll come up\n@chrisx aka MelonMan ^^\n\n",
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      "author": "alienposts",
      "body": "Welcome to steemit, happy to have you here\n\nI am @alienposts , my real name is achraf :)\nCheckout my blog posts, Enjoy your time here and let's get this party started :)",
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      "body": "Hello & Welcome to Steemit Chris ,\n\nI am @digital-gypsy - nice to meet you:)\n\nI think with your topics ( 3D printing, 3D scanning,..) you will reach out many people here and get their attention !\n\nif you like rainbow photos have a look at my account, just posted some nice Rainbow Photo\n\nGood Luck & Cheers",
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      "body": "It is hard to hide the fact that am a fan of 3D scanning. Being able to turn a physical object into a digital model is very convenient, especially if you have access to a 3D printer. However, there is one problem. Professional 3D scanning software can get expensive, and often needs very specialized equipment. Luckily for us hobbyists, there are some __great free tools__ out there to give us very similar results, and all we need is a camera and a few free programs.\n\nhttps://www.youtube.com/watch?v=YMnkrxfaMfg\n \nTo quickly recap, __photogrammetry is the process of creating a 3D model from a series of photographs__. It uses various algorithms to detect features in a picture, and compares them to features found in the other pictures. When it finds a set of common features between two pictures, it can then work out the different in orientation between them. With enough pictures around the object, and enough time to process, a 3D model can then be reconstructed from them.\n\nThe program I am using today is [VisualSFM (structure from motion)](http://ccwu.me/vsfm/). It is an amazing program which at the end produces either a point-cloud to be processed into a mesh using Meshlab, or further processed by PMVS/CMVS, but that is a topic for another post ;D.\n\nTo start, you can load in a series of images into VisualSFM. Be sure to remove any pictures which are out of focus. You want each picture to be at a different angle, but with small enough differences so that common features can be found between images. I aim for about 30-40 pictures in total.\n\nThe first processing step is to do feature detection and orientation determination. VisualSFM will use various algorithms to detect features (such as corners, edges, etc) in each image. If you are interested in learning more, you can read up on feature detectors such as _scale-invariant feature transform (SIFT)_ . It then will compare features in one image, to features in all the other images to see if it can find matches between images. If a match is found, its able to determine the difference in orientation based on the different orientation of the features. With enough matches, eventually you'll have a 360deg view of the object\n\nAfter that is done, time for dense reconstruction. Using that orientation data from the previous step, it produces a point cloud of the 3 dimensional representation of the object. These steps can take a bit of time to complete, but having a power GPU to handle the parallel processing certainly helps.\n\nCongratulations, you now have a 3D object produced using just a bunch of pictures! From here you can import it into other software to clean up the scan, add/modify the object, or even send it to a 3D printer. Why download a car, when you can scan one yourself!\n\nThe computer science behind the software is fascinating, I highly recommend anyone interested to look into the various techniques for __Structure from motion__. I'd love to dive into the topic deeper, but that'll have to be a post for another time! Thank you for reading, and let me know if you've had experience with photogrammetry, or any other kind of 3D scanning techniques!\n\n-Hoffman Engineering\n![HoffmanSiteLogoSmall.png](https://steemitimages.com/DQmSHtruSzmrVz7K2rQGGFgYziugSiciFQCMEVrnbHWW1sR/HoffmanSiteLogoSmall.png)",
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      "author": "steemitlotteries",
      "body": "Hello there @hoffmanengineer and welcome to **Steemit**! I just upvoted you!! I hope you enjoy your time here and make lots of $$$. If you're interested in lotteries, please check my profile out @steemitlotteries. I run **FULLY TRANSPARENT LOTTERIES** with promotional posts where I issue **FREE TICKETS** for those who help me curate my promotions. All the best! :)\n![](https://steemitimages.com/DQmbiXzgvBw7z38991d4A8tQn7T1xTwHnS4fQ2gSXLzY5tC/image.png)",
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      "author": "bearbear613",
      "body": "welcome!",
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      "author": "raptorman",
      "body": "Well I'll definitely be paying attention :) thanks!",
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      "author": "welcomebot",
      "body": "\n**Welcome to Steemit @hoffmanengineer :)**\n\n![Welcome Bot Banner](http://i.imgur.com/C3Gs3IS.png)\n\n[Make sure to participate in this weeks giveaway to get known in the community!](https://steemit.com/welcome/@reggaemuffin/welcome-giveaway-write-your-first-post-and-win-a-whale-vote-week-3)\n\nHere are some helpful resources to get you started: \n* [Complete Guide To What is Steem(it)](https://steemit.com/help/@reggaemuffin/complete-guide-to-what-is-steem-it)\n* [SteemPact – Do something good with one vote](https://steemit.com/steempact/@steempact/join-steempact-empowering-change-together-week-1)\n* [We all can do it!](https://steemit.com/witness-update/@thecryptodrive/steem-witness-vigil-first-we-kneel-then-we-rise)\n\n\n---\n\n_If you find this bot helpful, give it an upvote! It will continue to upvote introduction posts. Your upvote will give it more power in that. If you think you have something all new users should know, please tell._\n\n",
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