Kabushiki Kaisha Toshiba

Tsukasa Ike

Yasunobu Yamauchi

Ryuzo Okada

Toshiaki Nakasu

Hidetaka Ohira

Yasukazu Okamoto

Kazunori Imoto

Yojiro Tonouchi

Tomohiro Nakai

Toshifumi Ohtake

Akiyuki Tanizawa

Masahiro Fujita

Kei Sakamoto

Yasuhiro Taniguchi

Kazushige Ouchi

Mayumi Yuasa

Bjorn Stenger

Kentaro Yokoi

Takahiro Arai

Kanako Nakayama

Sawa Fuke

Mieko Asano

Toshihiko Manabe

Hisashi Kazama

Satoru Ishigaki

Yasuyuki Tsunoi

Nobuhisa Kishikawa

Izumi Fukunaga

Rei Sakuragi

According to one embodiment, a load estimation apparatus includes processing circuitry. The processing circuitry acquires sensor data from a measurement target, calculates one or more posture loads relating to one or more body parts of the measurement target based on the sensor data, and displays display data including a posture load graph in which the one or more posture loads are illustrated in time series.

Load estimation apparatus and method

According to one embodiment, a defect management apparatus includes a processor. The processor acquires first information and second information, the first information including first defect positions relating to defects detected with a first device for an inspection target and corresponding first labels indicating classifications of the defects, the second information including second defect positions relating to defects detected with a second device for the inspection target. The processor determines a first defect position corresponding to a second defect position as a corresponding defect position. The processor diverts the first label corresponding to the corresponding defect position as a second label of the second defect position.

Defect management apparatus, method and non-transitory computer readable medium

According to one embodiment, a load estimation apparatus includes processing circuitry. The processing circuitry acquires sensor data from a measurement target, estimates an operation of a body part of the measurement target, based on the sensor data, estimates an operation load of the body part, based on information on the operation, estimates a posture of the body part, based on the sensor data, estimates a posture load of the body part, based on information on the posture, estimates a first cumulative load, based on the operation load, and estimates a second cumulative load, which requires a longer load elimination time than the first cumulative load, based on the operation load and the posture load.

Load estimation apparatus, method and non-transitory computer-readable storage medium

According to one embodiment, an information processing apparatus includes processing circuitry. The processing circuitry acquires image data on a predetermined photographed area, generates part movement information on a plurality of parts of an object included in the image data, based on the image data, acquires sensor data from the object, generates sensor operation information on an operation of a sensor, based on the sensor data, and specifies a relationship between the object included in the image data and the sensor, based on the part movement information and the sensor operation information.

Information processing apparatus specifying a relationship between a sensor and an object included in image data, and method and non-transitory computer-readable storage medium

According to one embodiment, an information processing device includes a hardware processor configured to acquire operation cost information indicative of a relationship between a state of an operator and a period of time required for the operator to perform an operation from a storage that stores the operation cost information, acquire state information indicative of a state of a target operator, and calculate a period of time required for the target operator to perform a target operation based on the operation cost information and the state information.

Information processing device and method

According to one embodiment, there is provided an operation recognition device comprising a computer including a hardware processor. The hardware processor is configured to acquire movement information associated with a movement of a user, and area information corresponding to a first operation section; determine, based at least in part on the movement information and the area information corresponding to the first operation section, an estimated position corresponding to a subsequent operation by the user; and determine whether the subsequent operation by the user is directed to the first operation section based at least in part on the estimated position corresponding to the subsequent operation.

Operation recognition device and operation recognition method

A recognition device according to an embodiment described herein includes a hardware processor. The hardware processor generates a trajectory of a pointer based at least in part on information relating to a movement of the pointer, detects that the pointer contacts an operation surface, determines a detection time when the pointer contacts the operation surface, and determines a detection position of the pointer at the detection time, sets the detection position as a starting point, determines an ending point corresponding to the starting point based on at least the detection time or the detection position, and sets the trajectory from the starting point to the ending point as a target trajectory, and determines a command input by a user with a gesture of the pointer based on the target trajectory.

Recognition device, method, and storage medium

A recognition device includes an acquisition unit and a processor. The acquisition unit acquires first and second informations. The first information relates to a first signal corresponding to a state of a first portion of a body performing an action. The first signal is generated by a first element mounted to the first portion. The second information relates to a second signal corresponding to a state of a second portion. The second signal is generated by a second element mounted to the second portion. A relative positional relationship between the first portion and the second portion changes according to the action. The processor calculates a first feature based on the first information and a second feature based on the second information. The processor recognizes a type of the action based on a change of the first feature and a change of the second feature.

Recognition device, recognition method, and non-transitory recording medium

The acquiring unit is configured to acquire positions of a particular part of a user in time series. The calculator is configured to calculate a feature value of a motion of the particular part from the positions acquired in time series. The comparing unit configured to compare the feature value and a first threshold. The recognizing unit is configured to recognize the motion of the particular part using a first recognition method and a second recognition method which is different from the first recognition method. The control unit configured to control the recognizing unit to select the first recognition method for recognizing a position or a motion of the particular part when the feature value is smaller than the first threshold, and select the second recognition method when the feature value is equal to or larger than the first threshold.

Recognition apparatus

In an embodiment, a recognition apparatus includes: an obtaining unit configured to obtain positions of a specific part in a coordinate system having a first axis to an n-th axis (n&#x2267;2); a calculating unit configured to calculate a movement vector of the specific part; a principal axis selecting unit configured to select a principal axis; a turning point setting unit configured to set a position at which there is a change in the principal axis, and set a position at which there is a change; a section setting unit configured to set a determination target section, and set a previous section; a determining unit configured to calculate an evaluation value of the determination target section and an evaluation value of the immediately previous section and, determine which of the first axis to the n-th axis is advantageous; and a presenting unit configured to perform the determined result.

Recognition apparatus, method, and computer program product

According to one embodiment, an information search apparatus includes a generation unit, a selection unit, a search unit and a display unit. The generation unit generates recognition candidate character strings based on shapes of strokes and combinations of the shapes. The selection unit calculates reliability values for the recognition candidate character strings and selects search keys from the recognition candidate character strings. The search unit searches a database for second character strings including the search keys, and obtains one or more result character strings indicating search results of each of the search keys. The display displays the one or more result character strings corresponding to each of the search keys distinctively.

Information search apparatus and system

In an embodiment, a recognition apparatus includes an obtaining unit, a calculating unit, a principal axis selecting unit, a turning point setting unit, a section setting unit, and a determining unit. The obtaining unit obtains positions of a specific part in a coordinate system having a first axis to an n-th axis (n&#x2267;2). The calculating unit calculates a movement vector of the specific part. The principal axis selecting unit selects a principal axis. The turning point setting unit sets a position at which there is a change in the principal axis and sets a position at which there is a change. The section setting unit sets a determination target section, and sets a previous section. The determining unit calculates an evaluation value of the determination target section and an evaluation value of the immediately previous section and determines which of the first axis to the n-th axis is advantageous.

According to one embodiment, a time series information acquisition unit acquires time series information of a position or a size of a specific part of a user's body. An operation segment detection unit detects a movement direction of the specific part from the time series information, and detects a plurality of operation segments each segmented by two of a start point, a turning point and an end point of the movement direction. A recognition unit specifies a first operation segment to be recognized and a second operation segment following the first operation segment among the plurality of operation segments, and recognizes a motion of the specific part in the first operation segment by using a first feature extracted from the time series information of the first operation segment and a second feature extracted from the time series information of the second operation segment.

Apparatus and method for recognizing gesture, and non-transitory computer readable medium thereof

A gesture recognition apparatus including a detector, a controller and a gesture recognizer, and is able to detect a portion to be detected using an image captured at a first resolution without reducing the number of images to be entered per unit of time to an object detector by detecting an auxiliary portion instead when the portion to be detected is not detected at a second resolution, estimating the position of the auxiliary portion based on the position of the auxiliary portion, and extracting the periphery thereof from the image captured at the first resolution.

Gesture recognition apparatus and method thereof

In order to detect a specific detection object from an input image, a color serving as a reference is calculated in a reference image region. The difference for each color component between each pixel in the detection window and the reference color is calculated. Whether or not the detection object is included in the detection window is discriminated by a feature vector indicating how the difference is distributed in the detection window.

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Tokyo, Japan

Tsukasa Ike