A tracking device monitors a portion of a user's skin to infer a pose or gesture made by a body part of a user that engages the portion of the user's skin as the pose or gesture is made. For example, the tracking device monitors a portion of skin on a user's forearm to infer a pose or gesture made by the user's hand. The tracking device may include an illumination source that illuminates the portion of the user's skin. An optical sensor of the tracking device may capture images of the illuminated portion of skin. A controller of the tracking device infers a pose or gesture of the body part based in part on a model (e.g., a machine-learned model) and the captured images. The model may map various configurations of the user's skin to different poses or gestures of the body part.

The present application discloses a virtual object driving method, an apparatus, an electronic device and a readable storage medium, which relate to technical fields of artificial intelligence and deep learning. A specific implementing solution is as follows: obtaining a target image of a real object acquired by a camera when the real object makes a limb movement; inputting the target image into a coordinate acquisition model to obtain coordinates of a plurality of key points on a limb of the real object; determining a posture of the limb of the real object according to coordinates of each key point; driving, according to the posture of the real object, a virtual object displayed on a screen to present the limb movement of the real object. The method greatly reduces operation complexity and cost consumption when driving a virtual image.

Disclosed are methods, systems, and apparatus for monitoring delivered packages using video. A method includes obtaining a notification of a delivery of a package at a property that includes a first image depicting the package; obtaining a second image captured by a camera at the property; determining, using the first image and the second image, that the package has been delivered to the property; generating a package model that represents an appearance of the package; and tracking a location of the package for use in determining whether to provide an alert to a device about the location of the package. Determining that the package has been delivered to the property comprises: comparing the first image to a model of a scene of the property; determining that the first image satisfies similarity criteria for matching the model of the scene; and determining that the second image likely depicts the package.

System and methods of using an Artificial Intelligence (“AI”) trained model for classifying a patient's gait include receiving a video of a patient on the gait analysis device; classifying the patient's gait using a machine learning process on the gait analysis device; wherein the machine learning process is generated from an Artificial Intelligence (“AI”) trained model comprising: a key point trained model configured to generate a set of key points on a patient's body; an Angle-Based Approach configured to use the set of key points to classify the patient's gait based on angle calculations between key points; and a Key Point Path Track-Based Approach configured to use the key points to classify the patient's gait based on a patient's stance phase and swing phase.

A computer, including a processor and a memory, the memory including instructions to be executed by the processor to determine a vehicle six degree of freedom (DoF) pose based on an image where the six DoF pose includes x, y, and z location and roll, pitch, and yaw orientation and transform the vehicle six DoF pose into global coordinates based on a camera six DoF pose. The instructions can include further instructions to communicate to the vehicle the six DoF pose in global coordinates.

Systems and methods may be used for evaluating a patient after completion of an orthopedic surgery on a portion of a body part of the patient. In an example, the method includes capturing, using a camera of the device, a series of images of the patient in motion, determining respective lengths of the body part in each of the series of images based on comparing the body part in each of the series of images to a skeletal model, and identifying a maximum length of the body part from the respective lengths. The method may include displaying an indication corresponding to the maximum length.

Embodiments are disclosed for a subtitle generator for sign language content in digital videos. In some embodiments, a method of subtitle generation includes receiving an input video comprising a representation of one or more sign language gestures, extracting landmark coordinates associated with a signer represented in the input video, determining derivative information from the landmark coordinates, and analyzing the landmark coordinates and the derivative information by at least one gesture detection model to identify a first sign language gesture.

The present disclosure relates to systems and methods for analyzing and evaluating movement of a subjects and providing feedback. In some embodiments, a method comprises receiving one or more images of a body of the subject captured during performance of a physical movement by the subject; computing a model descriptive of positions and orientations of body parts of the subject based on the one or more images; generating a comparison of the positions and orientations to target positions and target orientations, respectively, for the physical movement; and generating a recommendation based on the comparison.

The present application provides a hand tracking method, device and system, wherein the method comprises: determining a current frame image corresponding to each tracking camera respectively; acquiring tracking information of a hand location corresponding to the to-be-detected frame image and two-dimensional coordinates of a preset quantity of skeleton points according to the current frame images and the tracking information of the last frame image of the current frame images; determining three-dimensional coordinates of the preset quantity of skeleton points according to the two-dimensional coordinates and pre-acquired tracking data of a head location corresponding to the hand location; carrying out smoothing filter processing on the three-dimensional coordinates of the skeleton points and historical three-dimensional coordinates of the last frame image so as to acquire processed stable skeleton points; and fusing, rendering and displaying the stable skeleton points and the tracking data of the head location so as to complete tracking and display of the hand location.

A system for performing synergistic object tracking and pattern recognition for event representation includes a computing platform having processing hardware and a system memory storing a software code. The processing hardware is configured to execute the software code to receive event data corresponding to one or more propertie(s) of an object, to generate, using the event data, a location data estimating a location of each of multiple predetermined landmarks of the object, and to predict, using one or both of the event data and the location data, a pattern corresponding to the propertie(s) of the object. The processing hardware is further configured to execute the software code to update, using the predicted pattern, the location data, and to merge the updated location data and the predicted pattern to provide merged data.