SYSTEMS AND METHODS FOR A 3D HOME MODEL FOR VISUALIZING PROPOSED CHANGES TO HOME
The following relates generally to light detection and ranging (LIDAR) and artificial intelligence (AI). In some embodiments, a system: receives LIDAR data generated from a LIDAR camera; measures a plurality of dimensions of a room of the home based upon processor analysis of the LIDAR data; builds a 3D model of the room based upon the measured plurality of dimensions; receives an indication of a proposed change to the room; modifies the 3D model to include the proposed change to the room; and displays a representation of the modified 3D model.
1 . A computer-implemented method for visualizing proposed changes to a home, the computer-implemented method comprising, via one or more processors, sensors, servers, and/or transceivers:
receiving light detection and ranging (LIDAR) data generated from a LIDAR camera;
measuring a plurality of dimensions of a room of the home based upon processor analysis of the LIDAR data;
building a 3D model of the room based upon the measured plurality of dimensions;
receiving object data comprising: (i) dimensional data of an object; (ii) a type of the object; and/or (iii) color data of the object;
with a trained machine learning algorithm, generating a recommendation for placement of the object in the room based upon: (i) the measured plurality of dimensions, and (ii) the received object data; and
displaying a representation of the 3D model including a representation of the recommendation for placement of the object.
2 . The computer-implemented method of claim 1 , wherein the displaying the representation of the 3D model comprises displaying a 2D image generated from the 3D model.
3 . The computer-implemented method of claim 1 , further comprising, via the one or more processors, transceivers, sensors, and/or servers, receiving navigation input;
wherein the displaying the representation of the 3D model comprises visually navigating through the 3D model based upon the received navigation input.
4 . The computer-implemented method of claim 1 , wherein the building of the 3D model further comprises building the 3D model further based upon preexisting home structural data.
5 . The computer-implemented method of claim 1 , further comprising, via the one or more processors, transceivers, sensors, and/or servers, receiving camera data including color data;
wherein the building of the 3D model further comprises:
deriving dimensions of a wall based upon processor analysis of the LIDAR data;
deriving a color of the wall based upon processor analysis of the camera data; and
filling, into the 3D model, the wall including the derived dimensions of the wall and the derived color of the wall.
6 . The computer-implemented method of claim 1 , wherein the object data comprises all of the: (i) dimensional data of an object; (ii) a type of the object; and/or (iii) color data of the object.
7 . The computer-implemented method of claim 1 , wherein the object data is received from a computing device of a human user, the computing device comprising: a computer, a smartphone, or a tablet.
8 . A computer system configured to visualize proposed changes to a home, the computer system comprising one or more processors, sensors, servers, and/or transceivers configured to:
receive light detection and ranging (LIDAR) data generated from a LIDAR camera;
measure a plurality of dimensions of a room of the home based upon processor analysis of the LIDAR data;
build a 3D model of the room based upon the measured plurality of dimensions;
receive object data comprising: (i) dimensional data of an object; (ii) a type of the object; and/or (iii) color data of the object;
with a trained machine learning algorithm, generate a recommendation for placement of the object in the room based upon: (i) the measured plurality of dimensions, and (ii) the received object data; and
display a representation of the 3D model including a representation of the recommendation for placement of the object.
9 . The computer system of claim 8 , the computer system further configured, via the one or more processors, sensors, servers, and/or transceivers, to display a 2D image generated from the 3D model.
10 . The computer system of claim 8 , the computer system further configured, via the one or more processors, sensors, servers, and/or transceivers, to:
receive navigation input; and
display the representation of the 3D model by visually navigating through the 3D model based upon the received navigation input.
11 . The computer system of claim 8 , the computer system further configured, via the one or more processors, sensors, servers, and/or transceivers, to build the 3D model by building the 3D model further based upon preexisting home structural data.
12 . The computer system of claim 8 , the computer system further configured, via the one or more processors, sensors, servers, and/or transceivers, to:
receive camera data including color data; and
build the 3D model by:
deriving dimensions of a wall based upon processor analysis of the LIDAR data;
deriving a color of the wall based upon processor analysis of the camera data; and
filling, into the 3D model, the wall including the derived dimensions of the wall and the derived color of the wall.
13 . The computer system of claim 8 , wherein the object data comprises all of the: (i) dimensional data of an object; (ii) a type of the object; and/or (iii) color data of the object.
14 . The computer system of claim 8 , the computer system further configured, via the one or more processors, sensors, servers, and/or transceivers, to receive the object data from a computing device of a human user, the computing device comprising: a computer, a smartphone, or a tablet.
15 . A computer system configured to visualize proposed changes to a home, comprising:
one or more processors; and
a non-transitory program memory coupled to the one or more processors and storing executable instructions that when executed by the one or more processors cause the computer system to:
receive light detection and ranging (LIDAR) data generated from a LIDAR camera;
measure a plurality of dimensions of a room of the home based upon processor analysis of the LIDAR data;
build a 3D model of the room based upon the measured plurality of dimensions;
receive object data comprising: (i) dimensional data of an object; (ii) a type of the object; and/or (iii) color data of the object;
with a trained machine learning algorithm, generate a recommendation for placement of the object in the room based upon: (i) the measured plurality of dimensions, and (ii) the received object data; and
display a representation of the 3D model including a representation of the recommendation for placement of the object.
16 . The computer system of claim 15 , wherein the executable instructions further cause the computer system to display a 2D image generated from the 3D model.
17 . The computer system of claim 15 , wherein the executable instructions further cause the computer system to:
receive navigation input; and
display the representation of the 3D model by visually navigating through the 3D model based upon the received navigation input.
18 . The computer system of claim 15 , wherein the executable instructions further cause the computer system to build the 3D model by building the 3D model further based upon preexisting home structural data.
19 . The computer system of claim 15 , wherein the executable instructions further cause the computer system to:
receive camera data including color data; and
build the 3D model by:
deriving dimensions of a wall based upon processor analysis of the LIDAR data;
deriving a color of the wall based upon processor analysis of the camera data; and
filling, into the 3D model, the wall including the derived dimensions of the wall and the derived color of the wall.
20 . The computer system of claim 15 , wherein the object data comprises all of the: (i) dimensional data of an object; (ii) a type of the object; and/or (iii) color data of the object.