Abstract: An information processing apparatus includes a network learning portion that performs learning of an appearance/position recognition network by constraining first to third weights and using a learning image, wherein the appearance/position recognition network has a foreground layer including a position node, a background layer including a background node, and an image layer including a pixel node, and is a neural network in which the position node, the background node, and the pixel node are connected to each other, and wherein the first weight is a connection weight between the position node and the pixel node, the second weight is a connection weight between the position node and the background node, and the third weight is a connection weight between the background node and the pixel node.

Abstract: There is provided a communication device including an acceptation unit configured to accept a service execution request for requesting execution of a service, a control unit configured to specify a service providing device to which a request for execution of a service provided by the service providing device is made based on a device record that includes the service and provision destination group information that indicates a provision destination group of the service, and the service execution request accepted by the acceptation unit, a transmission unit configured to transmit the service execution request to the service providing device specified by the control unit.

Abstract: A control system, method and computer program product cooperate to assist control for an autonomous robot. An interface receives recognition information from an autonomous robot, said recognition information including candidate target objects to interact with the autonomous robot. A display control unit causes a display image to be displayed on a display of candidate target objects, wherein at least two of the candidate target objects are displayed with an associated indication of a target object score.

Abstract: An information processing device includes: a foreground state estimating unit configured to estimate a foreground state of an image using an actual image which is an image to be actually observed; and a visible model updating unit configured to update a background visible model which is visibility of the background of an image and a foreground visible model which is visibility of the foreground using an estimation result of the foreground state.

Abstract: An information processing device includes a learning unit that performs, using an action performed by an object and an observation value of an image as learning data, learning of a separation learning model that includes a background model that is a model of the background of the image and one or more foreground model(s) that is a model of a foreground of the image, which can move on the background, in which the background model includes a background appearance model indicating the appearance of the background, and at least one among the one or more foreground model(s) includes a transition probability, with which a state corresponding to the position of the foreground on the background is transitioned by an action performed by the object corresponding to the foreground, for each action, and a foreground appearance model indicating the appearance of the foreground.

Abstract: There is provided an information processing apparatus including: an appliance power consumption estimating unit estimating power consumption of each of a plurality of appliances disposed inside a large region that is divided into a plurality of regions; an appliance presence probability estimating unit estimating appliance presence probabilities that are probabilities that the respective appliances are present in the respective regions; a responsible share deciding unit deciding responsible shares that are proportions for respective people when power consumption in each region is shared among people who may be present in the large region; and a power consumption allocating unit calculating an allocated amount of power consumption of each person based on the power consumption of each of the plurality of appliances, the appliance presence probabilities, and the responsible shares.

Abstract: A control system, a control method and a non-transitory computer readable storage medium cooperate to assist control for an autonomous robot. An interface receives recognition information from an autonomous robot (22), said recognition information including candidate target objects to interact with the autonomous robot (22). A display control unit (42) causes a display image to be displayed on a display of candidate target objects, wherein at least two of the candidate target objects are displayed with an associated indication of a target object score.

Abstract: There is provided an information processing apparatus including an information amount gain calculation unit that, on the assumption that a factor that could cause a state transition in a state transition model occurs and the state transition takes place as a result of an occurrence of the factor, determines an information amount gain, which is an information amount obtained by causing the factor to occur regarding a causal relationship between the factor and the state transition and observing a result thereof, an evaluation value calculation unit that determines an evaluation value to evaluate effectiveness of causing each of the factors to occur based on the information amount gain to acquire the causal relationship between the factor and the state transition, and a decision unit that decides the factor to be occurred based on the evaluation value.

Abstract: There is provided a robot device including an instruction acquisition unit that acquires an order for encouraging a robot device to establish joint attention on a target from a user, a position/posture estimation unit that estimates a position and posture of an optical indication device, which is operated by the user to indicate the target by irradiation of a beam, in response to acquisition of the order, and a target specifying unit that specifies a direction of the target indicated by irradiation of the beam based on an estimation result of the position and posture and specifies the target on an environment map representing a surrounding environment based on a specifying result of the direction.

Abstract: There is provided a control device including an image display unit configured to acquire, from a flying body, an image captured by an imaging device provided in the flying body and to display the image, and a flight instruction generation unit configured to generate a flight instruction for the flying body based on content of an operation performed with respect to the image captured by the imaging device and displayed by the image display unit.

Abstract: There is provided a robot device including an irradiation unit that irradiates pattern light to an external environment, an imaging unit that acquires an image by imaging the external environment, an external environment recognition unit that recognizes the external environment, an irradiation determining unit that controls the irradiation unit to be turned on when it is determined that irradiation of the pattern light is necessary based on an acquisition status of the image, and a light-off determining unit that controls the irradiation unit to be turned off when it is determined that irradiation of the pattern light is unnecessary or that irradiation of the pattern light is necessary to be forcibly stopped, based on the external environment.

Abstract: Provided is a robot device including an image input unit for inputting an image of surroundings, a target object detection unit for detecting an object from the input image, an object position detection unit for detecting a position of the object, an environment information acquisition unit for acquiring surrounding environment information of the position of the object, an optimum posture acquisition unit for acquiring an optimum posture corresponding to the surrounding environment information for the object, an object posture detection unit for detecting a current posture of the object from the input image, an object posture comparison unit for comparing the current posture of the object to the optimum posture of the object, and an object posture correction unit for correcting the posture of the object when the object posture comparison unit determines that there is a predetermined difference or more between the current posture and the optimum posture.

Abstract: A control system, a control method and a non-transitory computer readable storage medium cooperate to assist control for an autonomous robot. An interface receives recognition information from an autonomous robot (22), said recognition information including candidate target objects to interact with the autonomous robot (22). A display control unit (42) causes a display image to be displayed on a display of candidate target objects, wherein at least two of the candidate target objects are displayed with an associated indication of a target object score.

Abstract: Provided is a robot device including an image input unit for inputting an image of surroundings, a target object detection unit for detecting an object from the input image, an object position detection unit for detecting a position of the object, an environment information acquisition unit for acquiring surrounding environment information of the position of the object, an optimum posture acquisition unit for acquiring an optimum posture corresponding to the surrounding environment information for the object, an object posture detection unit for detecting a current posture of the object from the input image, an object posture comparison unit for comparing the current posture of the object to the optimum posture of the object, and an object posture correction unit for correcting the posture of the object when the object posture comparison unit determines that there is a predetermined difference or more between the current posture and the optimum posture.

Abstract: A control system, method and computer program product cooperate to assist control for an autonomous robot. The system includes a communications interface that exchanges information with the autonomous robot (22). A user interface displays a scene of location in which the autonomous robot (22) is positioned, and also receives an indication of a user selection of a user selected area within the scene. The communications interface transmits an indication of said user selected area to the autonomous robot (22) for further processing of the area by said autonomous robot (22).

Abstract: A data processing device includes a state value calculation unit which calculates a state value of which the value increases as much as a state with a high transition probability for each state of the state transition model, an action value calculation unit which calculates an action value, of which the value increases as a transition probability increases for each state of the state transition model and each action that the agent can perform, a target state setting unit which sets a state with great unevenness in the action value among states of the state transition model to a target state that is the target to reach by action performed by the agent, and an action selection unit which selects an action of the agent so as to move toward the target state.

Abstract: An HMM (Hidden Markov Model) learning device includes: a learning unit for learning a state transition probability as the function of actions that an agent can execute, with learning with HMM performed based on actions that the agent has executed, and time series information made up of an observation signal; and a storage unit for storing learning results by the learning unit as internal model data including a state-transition probability table and an observation probability table; with the learning unit calculating frequency variables used for estimation calculation of HMM state-transition and HMM observation probabilities; with the storage unit holding the frequency variables corresponding to each of state-transition probabilities and each of observation probabilities respectively, of the state-transition probability table; and with the learning unit using the frequency variables held by the storage unit to perform learning, and estimating the state-transition probability and the observation probability bas

Abstract: There is provided a gripping judgment apparatus including a plan unit that generates a target orbit for moving a gripping unit in a state in which an object as a gripping target is gripped by the gripping unit, an observation unit that measures movement of the gripping unit driven based on the target orbit, a gripping state judgment unit that judges whether or not an object as a gripping target is grippable based on a target value of the gripping unit derived from the target orbit and an actual measured value measured by the observation unit, and a gripping state change unit that changes a gripping state of an object gripped by the gripping unit based on a judgment result obtained by the gripping state judgment unit.

Abstract: There is provided an information processing apparatus including a manipulation model learning unit configured to learn a manipulation model regarding manipulation of a first object by a second object, by use of an actual image that is an actually observed image including the first object and the second object, the manipulation model associating a position and a change in state of the second object, when a state of the second object changes at a position in an object reference coordinate system with the first object regarded as a reference, with a change in state of the first object caused by the change in state of the second object.

Abstract: An object detecting device for detecting an object in a given gradation image. A scaling section generates scaled images by scaling down a gradation image input from an image output section. A scanning section sequentially manipulates the scaled images and cutting out window images from them and a discriminator judges if each window image is an object or not. The discriminator includes a plurality of weak discriminators that are learned in a group by boosting and an adder for making a weighted majority decision from the outputs of the weak discriminators. Each of the weak discriminators outputs an estimate of the likelihood of a window image to be an object or not by using the difference of the luminance values between two pixels. The discriminator suspends the operation of computing estimates for a window image that is judged to be a non-object, using a threshold value that is learned in advance.