Abstract: A display device includes a first conductive layer disposed on a substrate, a passivation layer disposed on the first conductive layer, a second conductive layer disposed on the passivation layer, a via layer disposed on the second conductive layer, a third conductive layer disposed on the via layer, the third conductive layer including a first electrode, a second electrode, a connection pattern, the first electrode, the second electrode, and the connection pattern being spaced apart from each other, and a light emitting element, a first end and a second end of the light emitting element being disposed on the first electrode and the second electrode, respectively, wherein the connection pattern electrically connects the first conductive layer and the second conductive layer through a first contact hole penetrating the via layer and the passivation layer.

Abstract: A display device according to an embodiment includes a light blocking layer disposed on a substrate; an oxygen supply layer disposed on and contacting the light blocking layer; a semiconductor layer disposed on the oxygen supply layer; and a light emitting diode electrically connected with the semiconductor layer. The semiconductor layer includes an oxide semiconductor, and the oxygen supply layer includes a metal oxide that includes at least one of indium, zinc, gallium, and tin.

Abstract: A method for automatic detection of CHF and AF with 12-bit RR interval time series using an electrocardiogram by using normalized RMSSD, sample entropy, and Shannon entropy, includes: (a) testing the electrocardiogram according to time from a subject; (b) calculating normalized RMSSD of data obtained at step (a); (c) calculating sample entropy value of the data obtained at step (a); (d) calculating Shannon entropy value for each of sections divided at step (a); and (e) comparing the normalized RMSSD, the sample entropy, and the Shannon entropy values calculated at steps (a),(b), and (c), and detecting CHF and AF.

Abstract: A Dan promotion test apparatus and a method thereof for recognizing Taekwondo Poomsae and automatically judging Dan promotion based on a skeleton of a human body using a depth camera are provided. The major configuration includes an object feature extraction unit for extracting features of an object input from the depth camera, a motion definition unit for defining various motions of the object, a motion recognition unit for recognizing a behavior of the object using the information obtained through the object feature extraction unit and the motion definition unit, and a judgment unit for judging correctness of a motion of the object confirmed by the motion recognition unit.

Abstract: There are provided an automatic vision sensor placement apparatus and method which analyze static spatial information in various aspects, calculate priorities of spaces using an agent that models the movement pattern of a user, suggest a method of effectively covering a given space, provide a camera placement method to appropriately install cameras with various levels of performance in a specified space, and calculate the optimal number of cameras to be installed based on installation cost.

Abstract: A method of recognizing a self location of an image acquisition device by acquiring an image of two or more reference objects is provided.

Abstract: There is provided a method of localizing an object comprising projecting an object located on an object plane and a reference point corresponding thereto on a virtual viewable plane and an actual camera plane; estimating coordinates of the reference point; and prescribing a relationship between a location of the object and the coordinates of the reference point.

Abstract: Provided are an apparatus and a method for tracking movements of objects to infer a topology of a network of multiple cameras. The apparatus infers the topology of the network formed of the multiple cameras that sequentially obtain images and includes an object extractor, a haunting data generator, and a haunting database (DB), and a topology inferrer. The object extractor extracts at least one from each of the obtained images, for the multiple cameras. The haunting data generator generates appearing cameras and appearing times at which the moving objects appear, and disappearing cameras and disappearing times at which the moving objects disappear, for the multiple cameras. The haunting DB stores the appearing cameras and appearing times and the disappearing cameras and disappearing times of the moving object, for the multiple cameras. The topology inferrer infers the topology of the network using the appearing cameras and appearing times and the disappearing cameras and disappearing times of moving objects.

Abstract: Provided are vision watching system and method for a safety hat. The vision watching system includes: a receiver which receives an image signal of a watching zone of a camera; a processor which determines whether an object of the image signal is a person, based on a size and an outline of the object and determines whether the person wears a safety hat, based on at least one or more of red (R), green (G), and blue (B) values of a head part of the person and a Hue value of Hue, Saturation, Value (HSV) of the head part; and a transmitter which outputs a Pan-Tilt-Zoom (PTZ) control signal of the camera to obtain a thumbnail image of the person when determining the person who does not wear the safety hat.

Abstract: There is provided a method of tracking an object in a three-dimensional (3-D) space by using particle filter-based acoustic sensors, the method comprising selecting two planes in the 3-D space; executing two-dimensional (2-D) particle filtering on the two selected planes, respectively; and associating results of the 2-D particle filtering on the respective planes.

Abstract: There are provided an automatic vision sensor placement apparatus and method which analyze static spatial information in various aspects, calculate priorities of spaces using an agent that models the movement pattern of a user, suggest a method of effectively covering a given space, provide a camera placement method to appropriately install cameras with various levels of performance in a specified space, and calculate the optimal number of cameras to be installed based on installation cost.

Abstract: An apparatus for actively tracking an object is provided. The apparatus includes a camera unit; a motor drive for changing a shooting direction of the camera unit; and a controller for acquiring a first comparative image and a second comparative image in sequence using the camera unit, comparing the first comparative image with the second comparative image, detecting a moving direction and a speed of an identical object existing in the first and second comparative images, determining an estimated location of the object after receipt of the second comparative image based on the detected moving direction and speed, and enlarging and capturing the object in the estimated location of the object.

Abstract: There is provided a method for real-time target detection comprising detecting a preprocessed pixel as a target and/or a background, based on a library, and refining the library by extracting a sample from the target or the background.

Abstract: There is provided a method for real-time target detection comprising detecting a preprocessed pixel as a target and/or a background, based on a library, and refining the library by extracting a sample from the target or the background.

Abstract: There is provided a method of localizing an object comprising projecting an object located on an object plane and a reference point corresponding thereto on a virtual viewable plane and an actual camera plane; estimating coordinates of the reference point; and prescribing a relationship between a location of the object and the coordinates of the reference point.

Abstract: There is provided a method of tracking an object in a three-dimensional (3-D) space by using particle filter-based acoustic sensors, the method comprising selecting two planes in the 3-D space; executing two-dimensional (2-D) particle filtering on the two selected planes, respectively; and associating results of the 2-D particle filtering on the respective planes.

Abstract: Provided are vision watching system and method for a safety hat. The vision watching system includes: a receiver which receives an image signal of a watching zone of a camera; a processor which determines whether an object of the image signal is a person, based on a size and an outline of the object and determines whether the person wears a safety hat, based on at least one or more of red (R), green (G), and blue (B) values of a head part of the person and a Hue value of Hue, Saturation, Value (HSV) of the head part; and a transmitter which outputs a Pan-Tilt-Zoom (PTZ) control signal of the camera to obtain a thumbnail image of the person when determining the person who does not wear the safety hat.

Abstract: A method of recognizing a self location of an image acquisition device by acquiring an image of two or more reference objects is provided.

Abstract: Provided are an apparatus and a method for tracking movements of objects to infer a topology of a network of multiple cameras. The apparatus infers the topology of the network formed of the multiple cameras that sequentially obtain images and includes an object extractor, a haunting data generator, and a haunting database (DB), and a topology inferrer. The object extractor extracts at least one from each of the obtained images, for the multiple cameras. The haunting data generator generates appearing cameras and appearing times at which the moving objects appear, and disappearing cameras and disappearing times at which the moving objects disappear, for the multiple cameras. The haunting DB stores the appearing cameras and appearing times and the disappearing cameras and disappearing times of the moving object, for the multiple cameras. The topology inferrer infers the topology of the network using the appearing cameras and appearing times and the disappearing cameras and disappearing times of moving objects.

Abstract: A method for classifying a plant leaf by utilizing the feature points of venation has been developed. A sample image of the venation can be extracted by utilizing a Curvature Scale Space (CSS) Corner Detection Algorithm. The sample image is treated to thicken the venation and increase the contrast through the retrieval unit prior to applying the Canny Edge Detection technology. The feature point, Branching Point and End Point is detected at each point where the calculated curvature angle is a local maximum. The distribution of the feature points of the extracted venation is calculated by applying a Parzen Window non-parametric estimation method.