Abstract: A writing instrument comprising a body, the body being provided with a writing tip and a position detection device, the position detection device being configured to provide data for determining a position of the body in a space, the position detection device comprising a tip pressure sensor, an inertial measurement unit, and a network of radio antennas.

Abstract: The pose and shape of a human body may be recovered based on joint location information associated with the human body. The joint location information may be derived based on an image of the human body or from an output of a human motion capture system. The recovery of the pose and shape of the human body may be performed by a computer-implemented artificial neural network (ANN) trained to perform the recovery task using training datasets that include paired joint location information and human model parameters. The training of the ANN may be conducted in accordance with multiple constraints designed to improve the accuracy of the recovery and by artificially manipulating the training data so that the ANN can learn to recover the pose and shape of the human body even with partially observed joint locations.

Abstract: An adaptor is provided for a shaving cartridge. The adaptor includes a frame extending along a longitudinal axis and a shaving aid coupled with the frame. The adaptor is configured to be reversibly mountable on a shaving cartridge perpendicular to the longitudinal axis.

Abstract: A shaving system, the system comprising a shaver including a shaver head, one or more sensors configured to detect a flow or sound of water or an orientation of the shaver and a processor configured to determine a duration and/or water usage during a shaving session and/or a rinsing session.

Abstract: A stylus for a touchscreen may comprise a barrel extending in a longitudinal direction, the barrel comprising a first end comprising an opening and a second end, the first end and the second end being, in the longitudinal direction, opposite to one another, and a first part and a second part, the first part including the first end and the second part including the second end, a first electronic tip received at least in part in the barrel and configured to have at least an in-use configuration in which the first electronic tip protrudes from the first part of the barrel through the opening, and an energy harvesting device comprising at least two of an energy harvesting element, a transducer, or an energy storage device.

Abstract: A method and system provide for on-board localization in a unmanned aerial system (UAS). A map image if generated (using previously acquired images) of an area that the UAS is overflying. The map image is then processed by orthorectifying, referencing the map image in a global reference frame, and generating an abstract map by detecting features and locating the features in the global reference frame. The UAS is then localized by acquiring camera images during flight, selecting a subset of the camera images as localization images, detecting on-board image features (in the localization images), mapping features from the detected on-board image features to the abstract map, deleting outliers to determine an estimated 3D pose, and refining the 3D pose. The localized UAS then used to autonomously navigate the UAS.

Abstract: Human mesh model recovery may utilize prior knowledge of the hierarchical structural correlation between different parts of a human body. Such structural correlation may be between a root kinematic chain of the human body and a head or limb kinematic chain of the human body. Shape and/or pose parameters relating to the human mesh model may be determined by first determining the parameters associated with the root kinematic chain and then using those parameters to predict the parameters associated with the head or limb kinematic chain. Such a task can be accomplished using a system comprising one or more processors and one or more storage devices storing instructions that, when executed by the one or more processors, cause the one or more processors to implement one or more neural networks trained to perform functions related to the task.

Abstract: A writing instrument comprising a body having an axis, a writing tip, a reservoir and at least one visual mark being a specific mark for augmented reality applications, the at least one visual mark being configured to be hidden/visible when the writing tip is distant from a writing surface and to be respectively visible/hidden when the writing tip is in contact with a writing surface, at least a portion of the body being configured to allow the at least one visual mark to adopt two states, visible and hidden configuration.

Abstract: A coupling mechanism for a shaving device having a first connector coupled with a second connector defining a channel, the second connector including an engagement surface within the channel. A retainer positioned between the first connector and the second connector, and a plunger that transitions between a first position and a second position. The engagement surface of the second connector engages the retainer when the plunger is in the first position and the engagement surface of the second connector disengages the retainer when the plunger is in the second position.

Abstract: A shaver, comprising a handle body, a cartridge coupled to the handle body, the cartridge including a skin care treatment head, a transducer configured to generate electrical energy from mechanical energy, thermal energy, sound or acoustic waves, magnetic field and/or radiofrequency energy; and a battery configured to receive electrical energy generated by the transducer.

Abstract: A shaving system, the system comprising a shaver including a shaver head, one or more sensors configured to detect a flow or sound of water or an orientation of the shaver and a processor configured to determine a duration and/or water usage during a shaving session and/or a rinsing session.

Abstract: The pose and shape of a human body may be recovered based on joint location information associated with the human body. The joint location information may be derived based on an image of the human body or from an output of a human motion capture system. The recovery of the pose and shape of the human body may be performed by a computer-implemented artificial neural network (ANN) trained to perform the recovery task using training datasets that include paired joint location information and human model parameters. The training of the ANN may be conducted in accordance with multiple constraints designed to improve the accuracy of the recovery and by artificially manipulating the training data so that the ANN can learn to recover the pose and shape of the human body even with partially observed joint locations.

Abstract: A shaving system, comprising a shaver including a handle a cartridge having at least one blade, the cartridge pivotably connected to the handle about a transverse axis of the handle; and a biasing element connected to the handle and connected to the cartridge, the biasing element being configured to move along a longitudinal axis of the handle in response to the cartridge pivoting about; a sensor configured to determine a pivot angle of the shaver cartridge relative to the handle; and a processor configured to receive information about the movement of the biasing element and determine an angle between the cartridge and the handle about the transverse axis based on the information.

Abstract: The pose and shape of a human body may be recovered based on joint location information associated with the human body. The joint location information may be derived based on an image of the human body or from an output of a human motion capture system. The recovery of the pose and shape of the human body may be performed by a computer-implemented artificial neural network (ANN) trained to perform the recovery task using training datasets that include paired joint location information and human model parameters. The training of the ANN may be conducted in accordance with multiple constraints designed to improve the accuracy of the recovery and by artificially manipulating the training data so that the ANN can learn to recover the pose and shape of the human body even with partially observed joint locations.

Abstract: A smart device comprising a first interface configured to transmit a first input from a user, a second interface configured to transmit a second input from the user, a digitizer positioned between the first interface and the second interface, and wherein the digitizer is configured to receive the first input from the user through the first interface and the second input from the user through the second interface.

Abstract: A razor includes a razor handle connected to a razor cartridge. The razor handle includes an elongated body extending in a longitudinal direction, and having an upper face and a lower face opposite the upper face. The upper face and lower face form at least a portion of an outermost surface of the razor handle. The outermost surface is provided with a first hole and a second hole. The first and second holes open on the outermost surface of the razor handle. The first hole extends from the upper face to the lower face of the outermost surface of the elongated body and includes an insert partially encapsulated within the first hole. The second hole includes an elongated bar or rib dividing the second hole into two parts. The elongated bar or rib extend in the longitudinal direction and is exposed on the upper face of the elongated body.

Abstract: Human mesh model recovery may utilize prior knowledge of the hierarchical structural correlation between different parts of a human body. Such structural correlation may be between a root kinematic chain of the human body and a head or limb kinematic chain of the human body. Shape and/or pose parameters relating to the human mesh model may be determined by first determining the parameters associated with the root kinematic chain and then using those parameters to predict the parameters associated with the head or limb kinematic chain. Such a task can be accomplished using a system comprising one or more processors and one or more storage devices storing instructions that, when executed by the one or more processors, cause the one or more processors to implement one or more neural networks trained to perform functions related to the task.

Abstract: A stylus for a touchscreen may comprise a barrel extending in a longitudinal direction, the barrel comprising a first end comprising an opening and a second end, the first end and the second end being, in the longitudinal direction, opposite to one another, and a first part and a second part, the first part including the first end and the second part including the second end, a first electronic tip received at least in part in the barrel and configured to have at least an in-use configuration in which the first electronic tip protrudes from the first part of the barrel through the opening, and an energy harvesting device comprising at least two of an energy harvesting element, a transducer, or an energy storage device.

Abstract: Human mesh model recovery may utilize prior knowledge of the hierarchical structural correlation between different parts of a human body. Such structural correlation may be between a root kinematic chain of the human body and a head or limb kinematic chain of the human body. Shape and/or pose parameters relating to the human mesh model may be determined by first determining the parameters associated with the root kinematic chain and then using those parameters to predict the parameters associated with the head or limb kinematic chain. Such a task can be accomplished using a system comprising one or more processors and one or more storage devices storing instructions that, when executed by the one or more processors, cause the one or more processors to implement one or more neural networks trained to perform functions related to the task.

Abstract: A smart device comprising a first interface configured to transmit a first input from a user, a second interface configured to transmit a second input from the user, a digitizer positioned between the first interface and the second interface, and wherein the digitizer is configured to receive the first input from the user through the first interface and the second input from the user through the second interface.