The present invention relates to landmark and/or temporal event detection. It is proposed to utilize previously learned spatial statistical correlations between multiple landmarks in order to regularize convolutional neural networks (CNNs) either as a post-processing step or during training in order to utilize anatomical prior knowledge, reduce the false-positive prediction rate, and/or increase the accuracy and stability of the algorithm. The proposed apparatus and method may also be applied to improve the detection of correlated events in e.g., time-series by leveraging prior knowledge.

A computer-implemented method can include receiving, by a computing system including one or more computing devices, data describing a media content item that includes a plurality of image frames for sequential display. The method can include inputting, by the computing system, the data describing the media content item into a machine-learned temporal analysis model that is configured to receive the data describing the media content item, and in response to receiving the data describing the media content item, output temporal analysis data that describes temporal information associated with sequentially viewing the plurality of image frames of the media content item. The method can include receiving, by the computing system and as an output of the machine-learned temporal analysis model, the temporal analysis data.

A computer-implemented method can include receiving, by a computing system including one or more computing devices, data describing a media content item that includes a plurality of image frames for sequential display. The method can include inputting, by the computing system, the data describing the media content item into a machine-learned temporal analysis model that is configured to receive the data describing the media content item, and in response to receiving the data describing the media content item, output temporal analysis data that describes temporal information associated with sequentially viewing the plurality of image frames of the media content item. The method can include receiving, by the computing system and as an output of the machine-learned temporal analysis model, the temporal analysis data.

The present technology relates to an information processing apparatus, an information processing method, and a program capable of easily setting a frame for starting predetermined processing in a moving image of a play in a ball game.

The information processing apparatus includes: an analysis unit that detects a trajectory of a ball in a first moving image; and a start frame setting unit that sets a start frame for starting predetermined processing among frames of the first moving image on the basis of a detection result of the trajectory of the ball in the first moving image. The present technology can be applied to, for example, a system that analyzes a rotation characteristic of a serve in table tennis.

This application provides a video information generation method, apparatus, and system and a storage medium. The video information generation method includes: obtaining a plurality of temporally consecutive target images; obtaining first information of a target object in the target images; and associating first information of a same target object located in different target images to generate target information. In the video information generation method provided in this application, the first information of the target object in the target images is obtained, and the first information of the same target object located in different target images is associated. In this way, target information with a relatively small amount of data can be obtained, thereby improving the efficiency of remotely viewing a video by a user.

This application provides a video information generation method, apparatus, and system and a storage medium. The video information generation method includes: obtaining a plurality of temporally consecutive target images; obtaining first information of a target object in the target images; and associating first information of a same target object located in different target images to generate target information. In the video information generation method provided in this application, the first information of the target object in the target images is obtained, and the first information of the same target object located in different target images is associated. In this way, target information with a relatively small amount of data can be obtained, thereby improving the efficiency of remotely viewing a video by a user.

The purpose of the present invention is to provide a fall risk evaluation system whereby risk of falling of an elderly person or other person to be managed can be easily evaluated on the basis of a captured image of daily life, instead of by a physical therapist, etc. To achieve this purpose, the present invention is a fall risk evaluation system comprising a stereo camera and a fall risk evaluation device, the fall risk evaluation device being provided with: a person authentication unit for authenticating a person to be managed who has been imaged by the stereo camera; a person tracking unit for tracking the person to be managed who is authenticated by the person authentication unit; an action extraction unit for extracting walking by the person to be managed; a feature value calculation unit for calculating a feature value of the walking extracted by the action extraction unit; an integration unit for generating integrated data obtained by integrating the outputs of the person authentication unit, the person tracking unit, the action extraction unit, and the feature value calculation unit; a fall index calculation unit for calculating a fall index value of the person to be managed, on the basis of a plurality of integrated data generated by the integration unit; and a fall risk evaluation unit for comparing the fall index value calculated by the fall index calculation unit and a threshold value to evaluate the risk of falling of the person to be managed.

In order to monitor operation situations of site resources at a construction site efficiently, a measuring system uses a surveying apparatus 100 including a camera and a position-determining function using laser light, and the measuring system includes a photographing means for continuously photographing construction machines 201 to 204 which are site resources for performing operations at a construction site by the camera, a recognizing means recognizing the site resources in photographed images obtained by the photographing, a tracking means for tracking the image of the site resources recognized in the multiple photographed images obtained by the continuous photographing, and a position-determining means collimating to the site resources which are objects for the tracking, and determining the positions of site resources by the position-determining function, in which the determining of positions is performed multiple times at intervals.

An apparatus to facilitate video motion smoothing is disclosed. The apparatus comprises one or more processors including a graphics processor, the one or more processors including circuitry configured to receive a video stream, decode the video stream to generate a motion vector map and a plurality of video image frames, analyze the motion vector map to detect a plurality of candidate frames, wherein the plurality of candidate frames comprise a period of discontinuous motion in the plurality of video image frames and the plurality of candidate frames are determined based on a classification generated via a convolutional neural network (CNN), generate, via a generative adversarial network (GAN), one or more synthetic frames based on the plurality of candidate frames, insert the one or more synthetic frames between the plurality of candidate frames to generate up-sampled video frames and transmit the up-sampled video frames for display.

Methods, systems, and apparatus are described herein for tracking objects and managing data. One or more objects may be determined in a first image. An avatar may be generated which is associated with the one or more objects in the first image. A second image may be received. The second image may comprise a change in at least one object of the one or more objects. Based on the change, in the at least one object, the avatar may be updated and the information kept for a predetermined period of time.