Samsung Electronics Co., Ltd.

Postech Academy-industry Foundation

Jae-Mo Sung

Won-Keun Kong

Sun-Jae Lee

Seungjin Choi

Seung-Jin Choi

Min-Young Mun

Sae-Hun Kim

An apparatus for recognizing a user's motions based on sensor information and label information, a method for establishing an ONMF-based basis matrix, and a method for establishing an OSSNMF-based basis matrix are provided, where the basis matrices are used to extract motion features of the user. The apparatus for recognizing the user's motions may include a feature vector extractor configured to multiply a transposed matrix of an orthogonalized basis matrix by a sensor data matrix of frequency domain sensor data acquired from sensors to extract an ONMF-based feature vector and a multi-class classifier configured to use the extracted ONMF-based feature vector to classify the user's motion into a type from among types of a user's motions.

Method and apparatus for recognizing motion feature of user, using orthogonal semisupervised non-negative matrix factorization (OSSNMF)-based feature data

A mobile device and operating method provides information by automatically recognizing a user intention. The mobile device includes a sensor configured to sense a user's eye movement, an event detector configured to detect an event by inferring a user intention based on the user's eye movement, an application function executor configured to execute a function of an application in response to the detected event. The mobile device may further include a display configured to display results of function execution.

Apparatus and method for providing information by recognizing user's intentions

A user activity real-time recognition apparatus and method are provided and include a collector configured to collect a frequency-domain signal for each user activity and to generate learning data based on the frequency-domain signal. The apparatus and method also include an extractor configured to extract a user activity feature from the frequency-domain signal based on an activity feature extracting model. The activity feature extracting model is learned based on the learning data from the collector. The apparatus and method further include a classifier configured to analyze the user activity feature to classify a user activity pattern based on an activity pattern classifying model and configured to transmit the classified user activity pattern to an application device.

Apparatus and method for recognizing user activity

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Hwaseong-si, South Korea

Jae-Mo Sung