elkraneo’s avatarelkraneo’s Twitter Archive—№ 4,420

        1. The paper about RoomPlan is fascinating to read. The result may seem simple, but it is the output of carefully designed and optimized steps that open the door for improved semantic understanding of physical contexts. machinelearning.apple.com/research/roomplan #AR #XR #Roomplan #a11y #accessibility
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      1. …in reply to @elkraneo
        Roomplan uses camera and LiDAR to make a 3D floor plan of a room (including dimensions and types of furniture). The system is made up of two parts:  - 3D room layout estimation (RLE) - 3D object-detection pipeline (3DOD)
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    1. …in reply to @elkraneo
      Room Layout Estimation (RLE) first finds the walls and openings, and then the result is used to figure out if the openings are doors or windows.
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  1. …in reply to @elkraneo
    3D Object Detection (3DOD) goes through a three-step process that first recognizes and categorizes objects locally, then globally for more information, and finally uses a box fusion process to create the dollhouse result, or 3D representation of the whole room.
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    1. …in reply to @elkraneo
      The making of an L-shaped sofa is an example of a relationship between objects during the fusion step. Also, if the object is not intersecting with any wall, then the correlation is calculated by aligning it with the closest one.
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      1. …in reply to @elkraneo
        🪴🪑📦 Chair’s category seems to be the most difficult to identify (83% precision) due to heavy occlusion or crowded arrangement.
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