Abstract: An apparatus for calibrating a driver monitoring camera may include: a camera configured to capture an image of a driver's face; a control unit configured to receive the captured image from the camera, and detect the face to determine a face position; and a display unit configured to display the determination result of the face position by the control unit.

Abstract: An apparatus for calibrating a driver monitoring camera may include: a camera configured to capture an image of a driver's face; a control unit configured to receive the captured image from the camera, and detect the face to determine a face position; and a display unit configured to display the determination result of the face position by the control unit.

Abstract: A face recognition technology using physiognomic feature information, which can improve the accuracy of face recognition. For this, the face recognition method using physiognomic feature information includes defining standard physiognomic types for respective facial elements, capturing a facial image of a user, detecting information about facial elements from the facial image, and calculating similarity scores relative to the standard physiognomic types for respective facial elements of the user based on the facial element information.

Abstract: A face recognition technology using physiognomic feature information, which can improve the accuracy of face recognition. For this, the face recognition method using physiognomic feature information includes defining standard physiognomic types for respective facial elements, capturing a facial image of a user, detecting information about facial elements from the facial image, and calculating similarity scores relative to the standard physiognomic types for respective facial elements of the user based on the facial element information.

Abstract: An apparatus includes an image receiving module configured to collect a depth image provided from a camera, a human body detection module configured to detect a human body from the collected depth image, and an activity recognition module configured to recognize an action of the human body on the basis of a 3-dimensional action volume extracted from the human body and a previously learned action model.

Abstract: An apparatus includes an image receiving module configured to collect a depth image provided from a camera, a human body detection module configured to detect a human body from the collected depth image, and an activity recognition module configured to recognize an action of the human body on the basis of a 3-dimensional action volume extracted from the human body and a previously learned action model.

Abstract: Disclosed is a method of sequencing character information in order to increase precision of character recognition. The method includes: a pre-processing that extracts character information from an image to binarize the extracted character information through a predetermined threshold and extracts and thins a center line of the binarized character information; normalizing the pre-processed character information to character information according to a predetermined criteria; and sequencing the normalized character information using structural features including an end point or a divergence point of the character information. The present invention suggests an angle normalization method of input character information, a structural feature position determining method, and a structural feature numeral string generating method to strongly recognize characters configured by various fonts obtained from a natural scene regardless of an angle or a size of the characters.

Abstract: A human information recognition method includes analyzing sensor data from multi-sensor resource placed in a recognition space to generate human information based on the sensor data, the human information including an identity, location and activity information of people existed in the recognition space. Further, the human information recognition method includes mixing the human information based on the sensor data with human information, the human information being acquired through interaction with the people existed in the recognition space; and storing a human model of the people existed in the recognition space depending on the mixed human information in a database unit.

Abstract: Disclosed is a method of detecting an upper body. The method includes detecting an omega candidate area including a shape formed of a face and a shoulder line of a human from a target image, cutting the target image into the upper body candidate area including the omega candidate area, detecting a human face from the upper body candidate area, and judging whether the upper body of the human is included in the target image according to the result of detecting the human face.

Abstract: The present invention detects a candidate ROI group associated with character strings/figure strings on the basis of a result acquired through prior learning of various types of license plates, verifies the interested region candidate group detected by using at least one condition of five predetermined conditions, and determines an MBR region in the selected ROI region from the verified interested region candidate group by considering a ratio between the height and width of the ROI region to recognize the license plate for the automobile. According to the present invention, it is possible to automatically detect the location of the license plate regardless of various types of license plate specifications defined for each of countries.

Abstract: Disclosed is a method of sequencing character information in order to increase precision of character recognition. The method includes: a pre-processing that extracts character information from an image to binarize the extracted character information through a predetermined threshold and extracts and thins a center line of the binarized character information; normalizing the pre-processed character information to character information according to a predetermined criteria; and sequencing the normalized character information using structural features including an end point or a divergence point of the character information. The present invention suggests an angle normalization method of input character information, a structural feature position determining method, and a structural feature numeral string generating method to strongly recognize characters configured by various fonts obtained from a natural scene regardless of an angle or a size of the characters.

Abstract: Disclosed are an apparatus for extracting a character area in a vehicle number plate and a method thereof. An apparatus for extracting a character area in a vehicle number plate according to an exemplary embodiment of the present invention includes a candidate area extracting unit configured to extract a plurality of character candidate areas from a vehicle number plate image using a plurality of algorithms; a filtering unit configured to determine a final character candidate area from the plurality of extracted character candidate areas; and a character area selecting unit configured to select a final character area from the final character candidate area using geometric information of blobs.

Abstract: A security control service system includes: a track security apparatus for traveling along a track installed in a place to be secured, and obtaining and transmitting security information to a security control apparatus; an autonomous mobile robot apparatus for traveling along the track together with the track security apparatus or freely traveling in the place to be secured, and obtaining and transmitting security information to the security control apparatus; and the security control apparatus for transmitting a control command for security control to the track security apparatus or the autonomous mobile robot apparatus after analyzing the security information.

Abstract: Disclosed is a method of detecting an upper body. The method includes detecting an omega candidate area including a shape formed of a face and a shoulder line of a human from a target image, cutting the target image into the upper body candidate area including the omega candidate area, detecting a human face from the upper body candidate area, and judging whether the upper body of the human is included in the target image according to the result of detecting the human face.

Abstract: Disclosed is a method of extracting a text area, the method including generating a text area prediction value within an input second image based on a plurality of text area data stored in a database including geometric information about a text area of a first image, generating a text recognition result value by determining whether a text is recognized with respect to a probable text area within the input second image, and selecting a text area within the second image by combining the generated text area prediction value and text recognition result value.

Abstract: The present invention detects a candidate ROI group associated with character strings/figure strings on the basis of a result acquired through prior learning of various types of license plates, verifies the interested region candidate group detected by using at least one condition of five predetermined conditions, and determines an MBR region in the selected ROI region from the verified interested region candidate group by considering a ratio between the height and width of the ROI region to recognize the license plate for the automobile. According to the present invention, it is possible to automatically detect the location of the license plate regardless of various types of license plate specifications defined for each of countries.