Abstract: The system comprises a plurality of actuators, which are operable to receive instructions and coordinate an actuation sequence. The system comprises a clamping mechanism, including at least one of the plurality of actuators and at least one clamping block. The system comprises a cutting mechanism, which cuts an insulation layer of a multiple conductor cable and includes at least one cutting blade. The system may comprise a control system, which comprises a plurality of controllers, a non-transitory readable medium storing instructions. The control system may receive cable parameters of the multiple conductor cable, including cable diameter and conductor quantity. The control system may activate the clamping mechanism and cutting mechanism. The control system may cause the clamping mechanism to rotate about a pivot point. The control system may remove a section of insulation from the multiple conductor cable based on the rotation of the clamping mechanism.

Abstract: A TV lift assist device and methods of operation and assembly thereof are described. The device includes a TV Holder Assembly (“TVHA”), a riser assembly, and a stand assembly. The stand assembly include a center rail assembly and two outrigger rail assemblies coupled thereto. The outrigger rail assemblies extend from front to end, include a top and a bottom surface, a front foot pad, a Leg Height Adjustment Assembly, a first adjustable leg coupled to the first LHAA, and an end foot pad coupled to a bottom surface of the first adjustable leg. The LHAA facilitates levelling of the stand assembly by extensions or retractions of the first adjustable leg within the first LHAA when the first front foot pad is resting on a first surface at a first elevation and the first end foot pad is resting on a second surface at a second elevation.

Abstract: The present disclosure provides a method (500) comprising receiving (510) images (e.g., 125A to 125G) of an object (110), the images (e.g., 125A to 125G) comprising first and second images. The method (500) then determines (530) feature points (810, 820) of the object (110) using the first images and determines (530, 540, 550) a three-dimensional reconstruction of a scene having the object (110). The method (500) then proceeds with aligning (560) the three-dimensional reconstruction with a three-dimensional mesh model of the object (110). The alignment can then be used to map (570) pixel values of pixels of the second images onto the three-dimensional mesh model. The directional radiosity of each mesh element of the three-dimensional mesh model can then be determined (580) and the hemispherical radiosity of the object (110) is determined (590) based on the determined directional radiosity.

Abstract: The present disclosure provides a method (500) comprising receiving (510) images (e.g., 125A to 125G) of an object (110), the images (e.g., 125A to 125G) comprising first and second images. The method (500) then determines (530) feature points (810, 820) of the object (110) using the first images and determines (530, 540, 550) a three-dimensional reconstruction of a scene having the object (110). The method (500) then proceeds with aligning (560) the three-dimensional reconstruction with a three-dimensional mesh model of the object (110). The alignment can then be used to map (570) pixel values of pixels of the second images onto the three-dimensional mesh model. The directional radiosity of each mesh element of the three-dimensional mesh model can then be determined (580) and the hemispherical radiosity of the object (110) is determined (590) based on the determined directional radiosity.

Abstract: In one embodiment, a method includes receiving, from one or more sensors, biomechanical data of a first user performing a plurality of actions of a first action-type and outcome data of a plurality of outcomes corresponding to the respective plurality of actions. A plurality of sets of action-parameter values may be determined based on the received biomechanical data, where each of the sets of action-parameter values corresponds to a respective action of the plurality of actions. An athletic-performance model of the first user may be generated based on the plurality of sets of action-parameter values. The athletic-performance model may be a statistical model including probabilities computed with respect to the sets of action-parameter values and the outcome data.

Abstract: In one embodiment, a method includes accessing an athletic-performance model of a first user, where the model is based on a plurality of sets of action-parameter values of action parameters of the first user. The action-parameter values may be determined based on biomechanical data of the first user performing a plurality of actions of a first action-type and outcome data of each action. A current skill level of the first user may be determined based on a measure of variances associated with action parameters of the first action-type. Target ranges of action-parameter values may be calculated for action parameters based on the athletic-performance model. Each target range may be based on a measure of probability with respect to the particular action parameters and the outcome data. A report of athletic-performance feedback may be generated and may include current skill level information and the target ranges of action-parameter values.

Abstract: In one embodiment, a method includes accessing an athletic-performance model of a first user, where the model is based on a plurality of sets of action-parameter values of action parameters of the first user. The action-parameter values may be determined based on biomechanical data of the first user performing a plurality of actions of a first action-type and outcome data of each action. A current skill level of the first user may be determined based on a measure of variances associated with action parameters of the first action-type. Target ranges of action-parameter values may be calculated for action parameters based on the athletic-performance model. Each target range may be based on a measure of probability with respect to the particular action parameters and the outcome data. A report of athletic-performance feedback may be generated and may include current skill level information and the target ranges of action-parameter values.

Abstract: In one embodiment, a method includes receiving, from one or more sensors, biomechanical data of a first user performing a plurality of actions of a first action-type and outcome data of a plurality of outcomes corresponding to the respective plurality of actions. A plurality of sets of action-parameter values may be determined based on the received biomechanical data, where each of the sets of action-parameter values corresponds to a respective action of the plurality of actions. An athletic-performance model of the first user may be generated based on the plurality of sets of action-parameter values. The athletic-performance model may be a statistical model including probabilities computed with respect to the sets of action-parameter values and the outcome data.

Abstract: In one embodiment, a method includes receiving, from one or more cameras, video data associated with a first user performing a plurality of actions of a first action-type. The cameras may be positioned to observe one or more biomechanical acts of the first user and an outcome for each action. The video data may be optically processed to determine a plurality of sets of action-parameter values corresponding to the respective plurality of actions. Each action-parameter value may be based on biomechanical acts for the respective action from the video data. Outcome data corresponding to the respective plurality of actions may be determined based on the video data. An athletic-performance model of the first user may be generated based on the sets of action-parameter values. The athletic-performance model may be a statistical model including probabilities computed with respect to the sets of action-parameter values and the outcome data.