An electronic device is provided. The electronic device includes a display, at least one processor, and at least one memory configured to store instructions that cause the at least one processor to obtain first information from a first still image frame that is included in a first moving image, obtain second information from the first moving image, identify at least one image function based on at least one of the first information or the second information, and control the display to display at least one function execution object for executing the at least one image function. Various other embodiments can be provided.

A training device according to an embodiment may be used for training for surgery using a surgical system that includes: a patient side apparatus including first and second robot arms; and a doctor side control apparatus including first and second input devices configured to operate the first and second robot arms respectively and a display. The training device may include: a training control unit configured to display, on the display, a first virtual surgical instrument that moves in response to operation on the first input device, and a second virtual surgical instrument that moves in response to operation on the second input device; and a storage storing therein a surgical video. The training control unit is configured to display on the display the surgical video stored in the storage with overlaying the first virtual surgical instrument and the second virtual surgical instrument on the surgical video.

A content model data base stores past target information, which includes past first video information acquired in advance, reference IDs, which are linked with the past target information, and which correspond to contents, and three or more levels of degrees of content association between the past target information and the reference IDs. A first acquiring unit acquires the target information from a user terminal, a first evaluation unit looks up the content model database and acquires ID information, which includes the degrees of content association between the target information and the reference IDs, and an output unit outputs the contents corresponding to the ID information. After the output from the output unit, the ID information, acquired by the first evaluation unit, is stored in an ID history unit.

A content model data base stores past target information, which includes past first video information acquired in advance, reference IDs, which are linked with the past target information, and which correspond to contents, and three or more levels of degrees of content association between the past target information and the reference IDs. A first acquiring unit acquires the target information from a user terminal, a first evaluation unit looks up the content model database and acquires ID information, which includes the degrees of content association between the target information and the reference IDs, and an output unit outputs the contents corresponding to the ID information. After the output from the output unit, the ID information, acquired by the first evaluation unit, is stored in an ID history unit.

A content model data base stores past target information, which includes past first video information acquired in advance, reference IDs, which are linked with the past target information, and which correspond to contents, and three or more levels of degrees of content association between the past target information and the reference IDs. A first acquiring unit acquires the target information from a user terminal, a first evaluation unit looks up the content model database and acquires ID information, which includes the degrees of content association between the target information and the reference IDs, and a judging unit judges the ID information. Contents that correspond to the ID information are output to the user terminal based on the result of judgment by the judging unit.

A content model data base stores past target information, which includes past first video information acquired in advance, reference IDs, which are linked with the past target information, and which correspond to contents, and three or more levels of degrees of content association between the past target information and the reference IDs. A first acquiring unit acquires the target information from a user terminal, a first evaluation unit looks up the content model database and acquires ID information, which includes the degrees of content association between the target information and the reference IDs, and a judging unit judges the ID information. Contents that correspond to the ID information are output to the user terminal based on the result of judgment by the judging unit.

A method for playing a video includes: detecting, on a display page of a target video, a first operation on the target video; generating a trigger signal in response to the first operation; acquiring, based on the trigger signal, at least one associated video of the target video; and displaying the at least one associated video.

A computer-implemented method, a computer program product, and a computer system for dynamically creating a composition reference video to support a user activity. In response to that a user selects a reference video for performing an activity, the computer system identifies a search query of a reference video. The computer system identifies personalized parameters of the user, based on a knowledge corpus user preferences of performing activities, and the search query. The computer system identifies appropriate videos and video transcripts in an online video repository and identifies textual contents through document and text search, based on a prediction about how the user is to perform the activity. The computer system draws series of images based on the textual contents. The computer system normalizes contents from the appropriate videos and the series of images and normalizes voices in the contents from the appropriate videos.

A computer-implemented method, a computer program product, and a computer system for dynamically creating a composition reference video to support a user activity. In response to that a user selects a reference video for performing an activity, the computer system identifies a search query of a reference video. The computer system identifies personalized parameters of the user, based on a knowledge corpus user preferences of performing activities, and the search query. The computer system identifies appropriate videos and video transcripts in an online video repository and identifies textual contents through document and text search, based on a prediction about how the user is to perform the activity. The computer system draws series of images based on the textual contents. The computer system normalizes contents from the appropriate videos and the series of images and normalizes voices in the contents from the appropriate videos.

Systems and processes are disclosed for controlling television user interactions using a virtual assistant. In an example process, a virtual assistant can interact with a television set-top box to control content shown on a television display. Speech input for the virtual assistant can be received from a device with a microphone. The speech input can comprise a query associated with content shown on the television display. A user intent of the query can be determined based on one or more of the content shown on the television display and a viewing history of media content. A result of the query can be caused to be displayed based on the determined user intent.