Abstract:
From plural observation features of a time series acquired by observing movements of a person, plural candidate segments are decided of a target action series containing plural respective actions expressing plural movements. Each of the plural candidate segments is divided into each action segment that is a time segment of the action, a likelihood corresponding to each of the plural actions computed for each of the action segments is normalized by action segment, and as an evaluation value a representative value is computed of normalized likelihood corresponding to each of the action segments selected from out of all of the respective action segments in the candidate segments based on an order of actions in the target action series. Being the target action series is determined in cases in which the evaluation value exceeds a common threshold.
Abstract:
A recording medium storing a program for causing a computer to execute processing including: acquiring a video data including frames each of which is associated with a time point and includes the video captured at the time point, by capturing a video at a site in which a person and an object exist; identifying a first relation by analyzing a first frame associated with a first time point, the first relation identifying an interaction between the object and the person in the first frame; identifying a second relation by analyzing a second frame associated with a second time point, the second relation identifying an interaction between the object and the person in the second frame; and specifying, based on the first and second relations, an action of the person on the object in a third frame associated with a third time point between the first and second time points.
Abstract:
An information reading system includes a passive-type IC tag that identifies a device installed on side of an environment, a tag reader that reads identification information of the passive-type IC tag, a sensor unit that detects a touch operation performed with respect to the passive-type IC tag, and a reading control unit that, when the sensor unit detects a touch operation, activates the tag reader and controls timing of reading the passive-type IC tag.
Abstract:
A non-transitory computer-readable recording medium storing a program for causing a computer to execute a process includes generating three-dimensional first skeleton information of a first person included in a first video by performing skeleton recognition, setting a first interesting region in a three-dimensional space for each of objects included in the first video based on design data, specifying a first object being used by the first person from among the objects included in the first video by using positional information of a hand of the first skeleton information and the first region of interest, acquiring a position distribution in which the hand is present in the three-dimensional space based on a trajectory of the part of the hand of the first skeleton information, and setting a second region of interest, in the three-dimensional space, that indicates that a person uses the first object, based on the position distribution.
Abstract:
A behavior recognition device acquires a video image in which a person is captured, and determines, by analyzing the acquired video image, whether or not an elemental behavior performed by the person is abnormal for each section that is obtained by dividing the video image. When the behavior recognition device determined that the elemental behavior is abnormal, the behavior recognition device extracts, from the acquired video image, the video image included in the section in which the elemental behavior is determined to be abnormal. The behavior recognition device transmits, in an associated manner, the extracted video image included in the section and a category of the elemental behavior that is determined to be abnormal.
Abstract:
A hidden semi-Markov model includes plural second hidden Markov models each containing plural first hidden Markov models using types of movement of a person as states. The plural second hidden Markov models each use partial actions that are parts of actions determined by combining plural movements as states. In the hidden semi-Markov model observation probabilities are leant for each type of the movements of the plural first hidden Markov models using unsupervised learning. The learnt observation probabilities are fixed, and input first supervised data is augmented to give second supervised data, and transition probabilities of the movements of the first hidden Markov models are learned by supervised learning in which the second supervised data is employed. The learnt observation probabilities and transition probabilities are employed to build the hidden semi-Markov model that is a model for estimating segments of the partial actions.
Abstract:
An information processing apparatus acquires video image data that includes target objects including a person and an object, and specifies, by inputting the acquired video image data to a first machine learning model, a relationship between each of the target objects included in the acquired video image data. The information processing apparatus specifies, by using a feature value of the person included in the acquired video image data, a behavior of the person included in the video image data. The information processing apparatus predicts, by inputting the specified behavior of the person and the specified relationship to a probability model, a future behavior or a future state of the person.