Provided is a control method including obtaining a first image; performing face recognition and gesture recognition on the first image; turning on a gesture control function when a first target face is recognized from the first image and a first target gesture is recognized from the first image; and returning to the act of obtaining the first image when the first target face is not recognized from the first image or the first target gesture is not recognized from the first image.

The present invention discloses a method, a device and a system for checkout, and belongs to the technical field of computer. The checkout method comprises: verifying whether a received unlocking request is sent by a pre-registered customer, and if so, issuing an unlocking instruction for opening an accommodating case in which a shelf for bearing the item is arranged and associating the customer with a take-up action or a put-back action aiming at an item; generating a shopping list of the customer, after identifying the take-up action or the put-back action and the item at which the take-up action or the put-back action aims; and performing checkout of the shopping list. The present invention further discloses a checkout device which comprises a registration module, a verification association module, a shopping list generation module and a checkout module. The present invention further discloses a checkout device which comprises a camera, a processor and a memory. The present invention further discloses a checkout system which comprises a client terminal, an accommodating case and a checkout device. According to the present invention, the selling process is friendly, the customer experience is good, a plurality of various items can be purchased in one transaction, and the purchasing procedure is convenient and fast.

Examples are disclosed that relate to representing recorded hand motion. One example provides a computing device comprising a logic subsystem and a storage subsystem comprising instructions executable by the logic subsystem to receive a recorded representation of hand motion determined relative to a virtual model aligned to a first instance of an object, receive image data corresponding to an environment, and recognize a second instance of the object in the environment. The instructions are further executable to align the virtual model to the second instance of the object, and output a parametric representation of hand motion for display relative to the virtual model as aligned to the second instance of the object, such that the parametric representation is spatially consistent with the recorded representation of hand motion relative to the virtual model as aligned to the first instance of the object.

A computer-implemented method for emotion detection and communication includes receiving host passenger data for a host passenger of a host vehicle and determining an emotion of the host vehicle based on the host passenger data. The method includes communicating the emotion of the host vehicle to one or more remote vehicles and an emotion of the one or more remote vehicles to the host vehicle. Further, the method includes generating an output based on the emotion of the host vehicle and the emotion of the one or more remote vehicles. The output is an interactive user interface providing an indication of the emotion of the host vehicle and an indication of the emotion of the one or more remote vehicle. The method includes rendering the output to a human machine interface device.

To accurately recognize observed objects. An observed-object recognition system includes an observation region estimation portion, an existence region estimation portion, and an object recognition portion. The observation region estimation portion estimates an observation region that is relatively highly likely to be an observation point in at least one first-person image in a first-person video (a video based on the first-person perspective). Based on the observation region, the existence region estimation portion estimates an existence region that belongs to the first-person image and causes an observed object to exist. The object recognition portion recognizes an object in the estimated existence region of the first-person image.

There is provided an information processing system, method, and program capable of displaying an image corresponding to an operation body in a certain place adaptively generated for an operation of the operation body in another place, the system including an information acquisition unit configured to acquire first transmission information according to an operation of an operation body related to a first user located in a first place, the first transmission information being for communication with a second user located in a second place, and an output control unit configured to display, on a display surface in the second place, an image corresponding to the operation body generated based on a pointing position of the operation body in the second place and a first virtual position of the first user in the second place, the pointing position and the first virtual position being specified based on the first transmission information.

Systems and methods are provided for enhanced animation generation based on using motion mapping with local bone phases. An example method includes accessing first animation control information generated for a first frame of an electronic game including local bone phases representing phase information associated with contacts of a plurality of rigid bodies of an in-game character with an in-game environment. Executing a local motion matching process for each of the plurality of local bone phases and generating a second pose of the character model based on the plurality of matched local poses for a second frame of the electronic game.

Described herein are assistant robots that anticipate needs of one or more people (or animals). The assistant robots may recognize a current activity, knowledge of the person's routines, and contextual information. As such, the assistant robots can provide or offer to provide appropriate robotic assistance. The assistant robots can learn users' habits or be provided with knowledge regarding humans in its environment. The assistant robots develop a schedule and contextual understanding of the persons' behavior and needs. The assistant robots may interact, understand, and communicate with people before, during, or after providing assistance. The robot can combine gesture, clothing, emotional aspect, time, pose recognition, action recognition, and other observational data to understand people's medical condition, current activity, and future intended activities and intents.

Systems and techniques for facilitating hand activity sensing are presented. In one example, a system obtains, from a wrist-worn computational device, hand activity data associated with a sustained series of hand motor actions in performance of a human task. The system also employs a machine learning technique to determine classification data indicative of a classification for the human task.

In some examples, a system processes event data and video frames produced by a program during execution of the program, the event data representing user actions with respect to a graphical user interface (GUI) of the program. The system identifies an area of the GUI that corresponds to a respective user action of the user actions, wherein identifying the area of the GUI uses a first video frame before an event corresponding to the respective user action, and a second video frame after the event corresponding to the respective user action. The system identifies, based on the identified area, a test object representing a user interface (UI) element, and generates a test script for testing the program, the test script including the test object.