{"id":6008,"date":"2023-03-16T02:40:20","date_gmt":"2023-03-15T17:40:20","guid":{"rendered":"https:\/\/open.datumo.com\/en\/?page_id=6008"},"modified":"2025-06-18T13:42:52","modified_gmt":"2025-06-18T04:42:52","slug":"posterior-body-image-dataset","status":"publish","type":"page","link":"https:\/\/open.datumo.com\/en\/?page_id=6008","title":{"rendered":"Posterior Body Image Dataset"},"content":{"rendered":"\t\t
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Posterior <\/span><\/span> Body <\/span><\/span> Image <\/span><\/span> Dataset <\/span><\/span> <\/h2><\/div><\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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An <\/span><\/span> image <\/span><\/span> dataset <\/span><\/span> of <\/span><\/span> the <\/span><\/span> posterior <\/span><\/span> side <\/span><\/span> of <\/span><\/span> the <\/span><\/span> human <\/span><\/span> body <\/span><\/span> is <\/span><\/span> essential <\/span><\/span> for <\/span><\/span> the <\/span><\/span> development <\/span><\/span> of <\/span><\/span> a <\/span><\/span> massage <\/span><\/span> robot <\/span><\/span> platform. <\/span><\/span> <\/p><\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\n\t\t\t\t\tDownload Datasets<\/span><\/a>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\tLearn about Datumo<\/span><\/a>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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Posterior Musculoskeletal Dataset<\/h5><\/div><\/div><\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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  • The collection and categorization of image data of the posterior side of the human body are necessary for the development of a massage robot platform.<\/span><\/p><\/li>

  • To facilitate musculoskeletal recognition in the massage robot platform, a diverse set of high-quality image data from various angles needs to be secured for robot learning.<\/span><\/li>

  • For the posterior side of the human body, data collection is performed for a total of 19 categories, including 12 upper body parts and 7 lower body parts. Each body part requires 2,000 images, resulting in a total of 38,000 images.<\/span><\/p><\/li><\/ul><\/p><\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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    Development <\/span><\/span> of <\/span><\/span> 'Muscular <\/span><\/span> Skeletal <\/span><\/span> Recognition <\/span><\/span> Technology' <\/span><\/span> on <\/span><\/span> the <\/span><\/span> back <\/span><\/span> of <\/span><\/span> the <\/span><\/span> human <\/span><\/span> body <\/span><\/span> <\/h3><\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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    Datumo provides high-quality training data for advanced artificial intelligence. This dataset was created as part of the <\/span>\u201cAI Dataset Sponsorship Program\u201d<\/span> organized by Datumo, in collaboration with Magenta Robotics.<\/span>
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    \"Since the mission involved directly capturing images of the human body, we encountered challenges with the slow data collection speed. Even though the target quantity of data was not large.<\/strong><\/p>

    The task of locating and annotating body parts involved some subjectivity, which made guide creation challenging. However, the fact that the client requested diverse data had a positive impact, despite the difficulties in guide production.\"<\/strong><\/p>

    Datumo \/ PM Park So-yeon<\/p><\/p><\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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    Dataset <\/span><\/span> specification <\/span><\/span> <\/h3><\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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    • Total number of photos: 2,549<\/span><\/p><\/li>

    • Number of bounding boxes: Approximately 25,000<\/span><\/p><\/li>

    • Data format: PNG, JSON<\/span><\/p><\/li><\/ul><\/p><\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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      Process <\/span><\/span> of <\/span><\/span> annotation <\/span><\/span> <\/h3><\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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      The data was collected and processed through the \"Cash Mission\" platform.<\/span><\/p>

      • Collection: Collecting posterior human body images<\/span><\/li>
      • Processing: Bounding box of posterior human body images<\/span><\/li><\/ul><\/p><\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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        • Opened separate missions on the Cash Mission platform for male and female participants, collecting a total of 10 photos per person (sitting back view, lying back view, standing back view)<\/span><\/p><\/li>

        • Utilized the collected image data to open processing missions on the Cash Mission platform, drawing bounding boxes around the keypoints (head, neck, shoulders, elbows, wrists, hips, calves, ankles) of the upper body and lower body.<\/span><\/p><\/li><\/ul><\/p><\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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          Datumo's crowd-sourcing platform, Cash Mission<\/strong>(App), was used for collection and processing of part of data<\/span><\/p><\/p><\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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          Guide Screens for Collection and Processing Tasks in the \"Cash Mission(App)\"<\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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          Sample Data<\/h4><\/div><\/div><\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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          {\"version\": \"4.5.6\", \"flags\": {}, \"shapes\": [{\"label\": \"Head\", \"points\": [[975.5119825708055, 193.33333333333331], [1159.9999999999993, 377.82135076252723]], \"shape_type\": \"rectangle\", \"flags\": {}}, 
          {\"label\": \"Neck\", \"points\": [[1013.4204793028322, 372.76688453159045], [1111.9825708061003, 471.3289760348584]], \"shape_type\": \"rectangle\", \"flags\": {}},
           {\"label\": \"LShoulder\", \"points\": [[677.2984749455333, 453.6383442265795], [811.241830065359, 587.5816993464052]], \"shape_type\": \"rectangle\", \"flags\": {}}, {\"label\": \"RShoulder\", \"points\": [[1245.9259259259277, 438.47494553376924], [1379.8692810457535, 572.4183006535951]], \"shape_type\": \"rectangle\", \"flags\": {}}, {\"label\": \"LElbow\", \"points\": [[513.0283224400878, 665.9259259259254], [657.080610021787, 809.9782135076248]], \"shape_type\": \"rectangle\", \"flags\": {}}, {\"label\": \"RElbow\", \"points\": [[1367.2331154684102, 630.5446623093676], [1523.9215686274517, 787.233115468409]], \"shape_type\": \"rectangle\", \"flags\": {}}, {\"label\": \"RWrist\", \"points\": [[1367.2331154684098, 782.1786492374724], [1475.9041394335513, 890.8496732026141]], \"shape_type\": \"rectangle\", \"flags\": {}}, 
          {\"label\": \"LHip\", \"points\": [[689.9346405228762, 635.5991285403044], [849.1503267973861, 794.8148148148142]], \"shape_type\": \"rectangle\", \"flags\": {}}, {\"label\": \"RHip\", \"points\": [[1218.126361655773, 605.272331154684], [1364.705882352941, 751.851851851852]], \"shape_type\": \"rectangle\", \"flags\": {}}, {\"label\": \"LKnee\", \"points\": [[745.5337690631808, 1009.6296296296299], [937.6034858387798, 1201.6993464052289]], \"shape_type\": \"rectangle\", \"flags\": {}}, 
          {\"label\": \"RKnee\", \"points\": [[1177.6906318082797, 991.9389978213507], [1379.8692810457526, 1194.1176470588234]], \"shape_type\": \"rectangle\", \"flags\": {}}, {\"label\": \"LAnkle\", \"points\": [[702.5708061002182, 1388.7145969498904], [887.058823529412, 1573.2026143790843]], \"shape_type\": \"rectangle\", \"flags\": {}}, {\"label\": \"RAnkle\", \"points\": [[1298.9978213507632, 1348.2788671023968], [1473.3769063180835, 1522.6579520697169]], \"shape_type\": \"rectangle\", \"flags\": {}}, 
          {\"label\": \"LWrist\", \"points\": [[644.757281553398, 805.242718446602], [720.7766990291261, 881.2621359223301]], \"shape_type\": \"rectangle\", \"flags\": {}}], \"imagePath\": \"lie_a_2.png\", \"imageData\": null, \"imageHeight\": 2320, \"imageWidth\": 2320}\n<\/pre><\/p><\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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          {\"version\": \"4.5.6\", \"flags\": {}, \"shapes\": [{\"label\": \"Neck\", \"points\": [[1307.553591160221, 595.0939226519336], [1406.73591160221, 694.2762430939225]], \"shape_type\": \"rectangle\", \"flags\": {}}, \n{\"label\": \"LShoulder\", \"points\": [[1026.0865105526357, 772.1094579227507], [1240.9041057285738, 986.9270530986885]], \"shape_type\": \"rectangle\", \"flags\": {}}, \n{\"label\": \"RElbow\", \"points\": [[1603.4087975879681, 1291.2519795979338], [1836.1278590285674, 1523.971041038533]], \"shape_type\": \"rectangle\", \"flags\": {}}, \n{\"label\": \"RHip\", \"points\": [[1453.4840176214286, 1450.1274926968044], [1643.6870966834572, 1640.330571758833]], \"shape_type\": \"rectangle\", \"flags\": {}}, \n{\"label\": \"LHip\", \"points\": [[1057.4140765157933, 1438.9390762813912], [1214.0519063315814, 1595.5769060971793]], \"shape_type\": \"rectangle\", \"flags\": {}}, \n{\"label\": \"Head\", \"points\": [[1281.162910204353, 376.02375024961736], [1453.0789323038007, 547.9397723490649]], \"shape_type\": \"rectangle\", \"flags\": {}}, \n{\"label\": \"RShoulder\", \"points\": [[1492.159965360946, 769.395275694333], [1696.265643066805, 973.500953400192]], \"shape_type\": \"rectangle\", \"flags\": {}},\n {\"label\": \"LElbow\", \"points\": [[1034.45249755142, 1201.488736532811], [1113.5749265426052, 1280.6111655239959]], \"shape_type\": \"rectangle\", \"flags\": {}}, \n{\"label\": \"RWrist\", \"points\": [[1778.7894221351617, 1641.057786483839], [1881.3555337904015, 1743.6238981390786]], \"shape_type\": \"rectangle\", \"flags\": {}}], \"imagePath\": \"sit_d_10.png\", \"imageData\": null, \"imageHeight\": 2992, \"imageWidth\": 2992}\n<\/pre><\/p><\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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          {\"version\": \"4.5.6\", \"flags\": {}, \"shapes\": [{\"label\": \"Head\", \"points\": [[1462.0776089343028, 206.98631699547195], [1664.2399646828392, 409.14867274400837]], \"shape_type\": \"rectangle\", \"flags\": {}}, \n{\"label\": \"Neck\", \"points\": [[1487.347903402869, 415.4662463611501], [1615.805233618085, 543.923576576366]], \"shape_type\": \"rectangle\", \"flags\": {}}, \n{\"label\": \"LShoulder\", \"points\": [[1192.527801269587, 546.0294344487467], [1318.8792736124221, 672.380906791582]], \"shape_type\": \"rectangle\", \"flags\": {}}, {\"label\": \"RShoulder\", \"points\": [[1712.6746957475918, 548.135292321127], [1841.1320259628078, 676.5926225363429]], \"shape_type\": \"rectangle\", \"flags\": {}}, {\"label\": \"LElbow\", \"points\": [[971.4127246696253, 885.0725519020211], [1106.1876285019828, 1019.8474557343787]], \"shape_type\": \"rectangle\", \"flags\": {}}, \n{\"label\": \"RElbow\", \"points\": [[1946.424919581838, 893.4959833915435], [2085.4115391589567, 1032.4826029686624]], \"shape_type\": \"rectangle\", \"flags\": {}}, {\"label\": \"LWrist\", \"points\": [[773.46208466585, 1148.3047859495948], [889.2842676467823, 1264.126968930527]], \"shape_type\": \"rectangle\", \"flags\": {}}, {\"label\": \"RWrist\", \"points\": [[2203.3395800122694, 1154.6223595667366], [2329.6910523551046, 1280.9738319095718]], \"shape_type\": \"rectangle\", \"flags\": {}}, {\"label\": \"LHip\", \"points\": [[1240.9625323343403, 1007.2123085000953], [1426.2780251038319, 1192.527801269587]], \"shape_type\": \"rectangle\", \"flags\": {}}, {\"label\": \"RHip\", \"points\": [[1670.5575382999805, 1005.1064506277147], [1860.0847468142333, 1194.6336591419674]], \"shape_type\": \"rectangle\", \"flags\": {}}, \n{\"label\": \"LKnee\", \"points\": [[1141.9872123324533, 1786.3797212809125], [1344.14956808099, 1988.5420770294493]], \"shape_type\": \"rectangle\", \"flags\": {}}, {\"label\": \"RKnee\", \"points\": [[1740.0508480885392, 1786.3797212809131], [1954.8483510713588, 2001.1772242637328]], \"shape_type\": \"rectangle\", \"flags\": {}}, {\"label\": \"LAnkle\", \"points\": [[1028.270887223901, 2546.5944132103045], [1207.2688063762514, 2725.5923323626553]], \"shape_type\": \"rectangle\", \"flags\": {}}, {\"label\": \"RAnkle\", \"points\": [[1841.132025962808, 2540.276839593163], [2028.5533766046801, 2727.6981902350353]], \"shape_type\": \"rectangle\", \"flags\": {}}], \"imagePath\": \"lie_a_1.png\", \"imageData\": null, \"imageHeight\": 3120, \"imageWidth\": 3120}\n<\/pre><\/p><\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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          lie_a_1.json<\/p><\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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          • Development of Musculoskeletal Recognition Technology for Application in Massage Robot Platforms<\/span><\/li>
          • Vision Sensor-based Human Back Visualization<\/span><\/li>
          • Development of Motion Recognition Massage Software based on a Dataset of Human Back Images<\/span><\/li>
          • Various fields in beauty, medical, and healthcare<\/span><\/li><\/ul><\/p><\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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            CC BY-SA<\/strong><\/p>
            Reusers are allowed to distribute, remix, adapt, and build upon the material in any medium or format, even commercially, so long as attribution is given to the creator. If you remix, adapt, or build upon the material, you must license the modified material under identical terms.<\/p>
            https:\/\/creativecommons.org\/licenses\/by-sa\/3.0\/deed.en<\/p><\/p><\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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            \n\t\t\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"Posterior  Body  Image  Dataset  An  image  dataset  of  the  posterior  side  of  the  human  body  is  essential  for  the  development  of  a  massage  robot  platform.  Download Datasets Learn about Datumo TAGS Bounding Box Image Human body Robot Posterior Musculoskeletal Dataset…","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"class_list":["post-6008","page","type-page","status-publish","hentry"],"yoast_head":"\nPosterior Body Image Dataset - Datumo Open Datasets for Data-Centric AI<\/title>\n<meta name=\"description\" content=\"An image dataset of the posterior side of the human body is essential for the development of a massage robot platform.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/open.datumo.com\/en\/?page_id=6008\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Posterior Body Image Dataset - 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