Abstract: A plurality of motion sensors capable of capturing IR video, depth video, and RGB images. Periodically emitting IR pulses. Capturing IR video, depth video, and RGB images of a user. Generating a point cloud of the user. Generating a 3D model of the user including the point cloud of the user. Inputting the IR video, depth video, and RGB images into a machine learning model. Estimating a set of joints of the user in the 3D model. Tracking, based on the estimated set of joints of the user in the 3D model, the user's motion over a period of time. Determining a number of repetitions of an exercise performed by the user. Determining a feedback value. Calculating, based on the number of repetitions and the feedback value, a user exercise score. Providing, via a graphical user interface, the user exercise score and the feedback value to the user.

Abstract: A plurality of motion sensors capable of capturing IR video, depth video, and RGB images. Periodically emitting IR pulses. Capturing IR video, depth video, and RGB images of a user. Generating a point cloud of the user. Generating a 3D model of the user including the point cloud of the user. Inputting the IR video, depth video, and RGB images into a machine learning model. Estimating a set of joints of the user in the 3D model. Tracking, based on the estimated set of joints of the user in the 3D model, the user's motion over a period of time. Determining a number of repetitions of an exercise performed by the user. Determining a feedback value. Calculating, based on the number of repetitions and the feedback value, a user exercise score. Providing, via a graphical user interface, the user exercise score and the feedback value to the user.

Abstract: A plurality of motion sensors capable of capturing IR video, depth video, and RGB images. Periodically emitting IR pulses. Capturing IR video, depth video, and RGB images of a user. Generating a point cloud of the user. Generating a 3D model of the user including the point cloud of the user. Inputting the IR video, depth video, and RGB images into a machine learning model. Estimating a set of joints of the user in the 3D model. Tracking, based on the estimated set of joints of the user in the 3D model, the user's motion over a period of time. Determining a number of repetitions of an exercise performed by the user. Determining a feedback value. Calculating, based on the number of repetitions and the feedback value, a user exercise score. Providing, via a graphical user interface, the user exercise score and the feedback value to the user.

Abstract: A free-standing A-frame exercise equipment cabinet comprising a first portion of the free-standing A-frame exercise equipment cabinet configured to removably house first exercise weight plates of a plurality of different sizes and a plurality of different weights. A second portion of the cabinet is configured to house a computer screen display. A third portion of the cabinet is configured to house at least one camera, one or more processors, and memory storing instructions that, when executed by the one or more processors, cause the cabinet to present a display on the computer screen display housed in the second portion of the cabinet. A fourth portion of the cabinet is configured to removably house at least one barbell and a plurality of dumbbells. A fifth portion of the cabinet comprises four legs of the cabinet that allow the cabinet to stand upright without additional support.