Bounding Box
Image
Human body
Robot
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.
- 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.
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.
Datumo provides high-quality training data for advanced artificial intelligence. This dataset was created as part of the “AI Dataset Sponsorship Program” organized by Datumo, in collaboration with Magenta Robotics.
"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.
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."
Datumo / PM Park So-yeon
Total number of photos: 2,549
Number of bounding boxes: Approximately 25,000
Data format: PNG, JSON
The data was collected and processed through the "Cash Mission" platform.
- Collection: Collecting posterior human body images
- Processing: Bounding box of posterior human body images
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)
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.
Datumo's crowd-sourcing platform, Cash Mission(App), was used for collection and processing of part of data
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{"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}
lie_a_2.json
{"version": "4.5.6", "flags": {}, "shapes": [{"label": "Neck", "points": [[1307.553591160221, 595.0939226519336], [1406.73591160221, 694.2762430939225]], "shape_type": "rectangle", "flags": {}},
{"label": "LShoulder", "points": [[1026.0865105526357, 772.1094579227507], [1240.9041057285738, 986.9270530986885]], "shape_type": "rectangle", "flags": {}},
{"label": "RElbow", "points": [[1603.4087975879681, 1291.2519795979338], [1836.1278590285674, 1523.971041038533]], "shape_type": "rectangle", "flags": {}},
{"label": "RHip", "points": [[1453.4840176214286, 1450.1274926968044], [1643.6870966834572, 1640.330571758833]], "shape_type": "rectangle", "flags": {}},
{"label": "LHip", "points": [[1057.4140765157933, 1438.9390762813912], [1214.0519063315814, 1595.5769060971793]], "shape_type": "rectangle", "flags": {}},
{"label": "Head", "points": [[1281.162910204353, 376.02375024961736], [1453.0789323038007, 547.9397723490649]], "shape_type": "rectangle", "flags": {}},
{"label": "RShoulder", "points": [[1492.159965360946, 769.395275694333], [1696.265643066805, 973.500953400192]], "shape_type": "rectangle", "flags": {}},
{"label": "LElbow", "points": [[1034.45249755142, 1201.488736532811], [1113.5749265426052, 1280.6111655239959]], "shape_type": "rectangle", "flags": {}},
{"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}
sit_d_10.json
{"version": "4.5.6", "flags": {}, "shapes": [{"label": "Head", "points": [[1462.0776089343028, 206.98631699547195], [1664.2399646828392, 409.14867274400837]], "shape_type": "rectangle", "flags": {}},
{"label": "Neck", "points": [[1487.347903402869, 415.4662463611501], [1615.805233618085, 543.923576576366]], "shape_type": "rectangle", "flags": {}},
{"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": {}},
{"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": {}},
{"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}
lie_a_1.json
- Development of Musculoskeletal Recognition Technology for Application in Massage Robot Platforms
- Vision Sensor-based Human Back Visualization
- Development of Motion Recognition Massage Software based on a Dataset of Human Back Images
- Various fields in beauty, medical, and healthcare
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