[{"data":1,"prerenderedAt":314},["ShallowReactive",2],{"project-10794668":3},{"id":4,"name":5,"line":6,"line_source":7,"title":8,"url":9,"domain":10,"maker":11,"posted_at":12,"year":13,"points":14,"comments":15,"rank_in_year":16,"shown_in_year":17,"top":18,"tier":19,"category":20,"subcategory":21,"format":22,"keywords":23,"reception":28,"sentiment":29,"stance_mix":30,"scored_comments":34,"aspects":35,"strip":43,"post_text":45,"what":46,"said":60,"maker_in_thread":192,"shape":202,"grid":207,"attempts":277,"same_week":278,"maker_shows":37,"maker_hidden":306,"reader_version":307,"card":308},"10794668","VoxelCamera","3D scanning with a mobile phone (YC Fellowship 2015)","title","Show HN: VoxelCamera – 3D scanning with a mobile phone (YC Fellowship 2015)","http:\u002F\u002Fvoxelcamera.co\u002F","voxelcamera.co","pondruska",1451152630,2015,37,35,769,2565,30,"shown","creative","3d scanning","mobile_app",[21,24,25,26,27],"photogrammetry","3d printing","volumetric capture","iphone","curious",-0.104,{"positive":31,"neutral":32,"mixed":31,"critical":33},2,15,3,22,{"idea":36,"execution":39,"design":40,"docs":41,"performance":42},{"positive":37,"critical":38},1,0,{"positive":38,"critical":37},{"positive":37,"critical":38},{"positive":38,"critical":37},{"positive":38,"critical":37},[33,38,37,38,38,38,38,38,33,38,33,38,38,38,33,33,33,33,44,33,33,33,33,38,37,38,37,33,44,33,33,33,33,33],5,null,{"problem":47,"audience":45,"pricing":45,"motivation":45,"time_to_build":45,"stack":57,"openness":58,"stage":59,"team_size":58},{"value":48,"source":49,"evidence":50},"Creating full 3D models of objects from a phone camera","maker",[51,54],{"id":52,"by":11,"text":53},"10796315","We like Seene but unlike only creating 2.5D pictures we aim for full 3D models one can further use for any purpose (such as 3D printing or creating digital content).",{"id":55,"by":11,"text":56},"10796839","Thanks, Structure From Motion is a broad term covering a number of different methods which were developed over years and our method is also a form of SFM. The main challenge here…",[],"unknown","beta",{"praise":61,"objections":78,"requests":117,"questions":146,"alternatives":165},[62],{"value":63,"source":64,"evidence":65},"Fun to use and impressive real-time results on an iPhone","commenter",[66,70,74],{"id":67,"by":68,"text":69},"10795523","clay_to_n","Reminds me of the iOS app Seene, which is like Instagram for 3D photos made on your phone: http:\u002F\u002Fseene.co\u002F Ultimately not much of a value prop for me, but was very fun to play…",{"id":71,"by":72,"text":73},"10795228","rememberlenny","Rudimentary Kinect with your iphone, without any additional hardware. Pretty cool",{"id":75,"by":76,"text":77},"10797206","Sir_Substance","Yeah, I'm at the point of running Agisoft Photoscan under wine, no results yet. But of course I won't get the heat-map quality indicator, which is the bit I really like about…",[79,90,100,111],{"value":80,"source":64,"evidence":81},"Scan quality is poor compared to depth sensors like Kinect",[82,86],{"id":83,"by":84,"text":85},"10795333","pontifier","The problem I see with all of these scanners is the lack of quality... Are they all based on the same feature tracking core? Why isn't anyone doing more innovative reconstruction…",{"id":87,"by":88,"text":89},"10795673","asadlionpk","Good work! Microsoft was\u002Fis working on something similar[1] I tried the app on a chair and an object on table. It's far from what kinect can do. I am optimistic about it though.…",{"value":91,"source":64,"evidence":92},"Not compatible with older iPads or non-iOS devices",[93,97],{"id":94,"by":95,"text":96},"10796933","3dfan","\"VocelCamera is not compatible with this iPad\" That's what I get on my iPad 2. Why?",{"id":98,"by":76,"text":99},"10797087","That's a sweet trick, but I don't have an iphone, and apparently it's not compatible with ipad 2's. Anyone know if there's an equivalent piece of software for a desktop computer,…",{"value":101,"source":64,"evidence":102},"Models cannot yet be exported",[103,107],{"id":104,"by":105,"text":106},"10795550","JorgeGT","Can the mesh be exported?",{"id":108,"by":109,"text":110},"10795830","lakySK","Not yet, unfortunately :( We'll be adding export to ply in the coming versions.",{"value":112,"source":64,"evidence":113},"Scanning is hard to get to 100% progress",[114],{"id":115,"by":72,"text":116},"10796380","Tried to use this twice today, but struggled to get it to 100% progress long enough. Video instructions would be good.",[118,129,139],{"value":119,"source":64,"evidence":120},"Export to PLY or other 3D printing formats",[121,125,128],{"id":122,"by":123,"text":124},"10795259","bcks","Ooh, please make it easy to export to a format I can load into a 3D printer.",{"id":126,"by":109,"text":127},"10795824","Hi bcks, we're working on it. We'll be releasing a new version that allows you to export to ply. We're also working on adding external 3D printing and delivery straight from the…",{"id":104,"by":105,"text":106},{"value":130,"source":64,"evidence":131},"Android version",[132,136],{"id":133,"by":134,"text":135},"10795338","zpr","Any plans for an android version?",{"id":137,"by":109,"text":138},"10795838","Unfortunately, we don't have enough time to add Android support at the moment, as we're focusing on improving the quality and disability for the existing app. In the longer term…",{"value":140,"source":64,"evidence":141},"Video instructions",[142,143],{"id":115,"by":72,"text":116},{"id":144,"by":11,"text":145},"10796394","Thanks, we will make one. Try to put the object on a newspaper or other well-textured surface. It usually helps.",[147,155],{"value":148,"source":64,"evidence":149},"How is this different from traditional structure-from-motion methods",[150,154],{"id":151,"by":152,"text":153},"10796659","joshvm","Cool to see it working at speed! The site mentions this is a new technology, how is this different from traditional SFM type algorithms which have been around for almost a decade…",{"id":55,"by":11,"text":56},{"value":156,"source":64,"evidence":157},"How does it handle fine detail such as hair",[158,162],{"id":159,"by":160,"text":161},"10797776","mandeepj","How you handle long hair in a picture?",{"id":163,"by":109,"text":164},"10797926","We don't have any special case processing, everything is handled the same way in the volumetric model, which makes the app really versatile. If you're expecting a scan detailed…",[166,170,177,181,185],{"value":167,"source":64,"evidence":168},"Seene",[169],{"id":67,"by":68,"text":69},{"value":171,"source":64,"evidence":172},"Mementify",[173],{"id":174,"by":175,"text":176},"10795734","fgd","A few years back (then) coworkers made a version of this called Mementify [0] which was derived from an EU research project called PHOV [1]. Quite interesting to see the idea pop…",{"value":178,"source":64,"evidence":179},"Microsoft MobileFusion",[180],{"id":87,"by":88,"text":89},{"value":182,"source":64,"evidence":183},"Agisoft Photoscan",[184],{"id":75,"by":76,"text":77},{"value":186,"source":64,"evidence":187},"LSD-SLAM",[188],{"id":189,"by":190,"text":191},"10795553","dllu","Most structure from motion or monocular SLAM algorithms use some kind of feature tracking and then estimate a dense reconstruction after they optimize the locations of all the…",{"comments":193,"answered":33,"key":194},7,[195,196,199],{"id":52,"text":53},{"id":197,"text":198},"10796390","The critical property of all similar systems is the way how you use it. Modern research systems, both based on depth sensors or cameras can in fact provide very good results if…",{"id":200,"text":201},"10796282","Right now the scanning works well for a limited number of scenarios (such as the ones shown on the page). We are working on improving the quality and expect it will grow over…",{"commenters":203,"max_depth":204,"maker_replies":193,"first_comment_mins":205,"lifespan_hours":206},18,4,168,23,[208,210,211,213,217,219,222,225,227,229,231,232,234,236,238,240,241,244,246,248,250,251,252,254,255,258,260,263,265,268,271,273,274,276],[67,38,33,209,68,38],"project\u002Fneutral\u002Fidea",[52,38,38,209,11,37],[83,37,37,212,84,38],"project\u002Fcritical\u002Fexecution",[214,37,38,215,216,38],"10795518","commenter\u002Fneutral\u002Fexecution","KaiserPro",[189,37,38,218,190,38],"commenter\u002Fneutral\u002Fnone",[220,37,38,218,221,38],"10795617","jasonwatkinspdx",[223,37,38,218,224,38],"10795670","emanuelev",[197,37,38,226,11,37],"project\u002Fneutral\u002Fexecution",[87,31,33,228,88,38],"project\u002Fmixed\u002Fexecution",[200,31,38,230,11,37],"project\u002Fneutral\u002Fperformance",[174,33,33,209,175,38],[233,33,38,230,11,37],"10796463",[235,204,38,218,160,38],"10796668",[237,204,38,226,11,37],"10796851",[133,44,33,239,134,38],"project\u002Fneutral\u002Fnone",[137,44,33,239,109,38],[98,242,33,243,76,38],6,"project\u002Fmixed\u002Fnone",[245,242,33,209,109,38],"10797183",[75,242,44,247,76,38],"project\u002Fpositive\u002Fdesign",[249,242,33,239,109,38],"10797979",[122,193,33,239,123,38],[126,193,33,239,109,38],[151,253,33,209,152,38],8,[55,253,38,230,11,37],[115,256,37,257,72,38],9,"project\u002Fcritical\u002Fdocs",[144,256,38,259,11,37],"project\u002Fneutral\u002Fdocs",[94,261,37,262,95,38],10,"project\u002Fcritical\u002Fperformance",[264,261,33,230,109,38],"10797076",[71,266,44,267,72,38],11,"project\u002Fpositive\u002Fidea",[269,266,33,270,109,38],"10795814","maker\u002Fneutral\u002Fnone",[104,272,33,239,105,38],12,[108,272,33,239,109,38],[159,275,33,226,160,38],13,[163,275,33,226,109,38],[],[279,284,289,294,297,302],{"id":280,"name":281,"points":282,"category":283},"10798916","CodeUpStart",95,"learning_science",{"id":285,"name":286,"points":287,"category":288},"10800603","CodeHalf",87,"productivity",{"id":290,"name":291,"points":292,"category":293},"10788083","nodejs-web-jade-scaffold",63,"dev_tools",{"id":295,"name":296,"points":292,"category":20},"10811325","Image-triangulation",{"id":298,"name":299,"points":300,"category":301},"10804853","Netflix Party",58,"consumer_social",{"id":303,"name":304,"points":305,"category":293},"10793564","GitHub Hovercard",40,false,"v2",{"id":309,"name":5,"line":6,"ai":306,"cat":20,"year":13,"points":14,"comments":15,"rec":28,"s":310,"top":18,"kw":311,"maker":11,"domain":10,"tier":19,"attempts":38,"strip":312,"url":9,"mix":313,"praise":63,"objection":80,"sub":21},10794668,-0.1,[21,24,25,26,27],"3010000030300033335333301013533333",[31,32,31,33],1794036538916]