Abstract: Disclosed are multiple object detection method and apparatus. The multiple object detection apparatus includes a feature map extraction unit for extracting a plurality of multi-scale feature maps based on an input image, and a feature map fusion unit for generating a multi-scale fusion feature map including context information by fusing adjacent multi-scale feature maps among the plurality of multi-scale feature maps generated by the feature map extraction unit.

Abstract: Disclosed are multiple object detection method and apparatus. The multiple object detection apparatus includes a feature map extraction unit for extracting a plurality of multi-scale feature maps based on an input image, and a feature map fusion unit for generating a multi-scale fusion feature map including context information by fusing adjacent multi-scale feature maps among the plurality of multi-scale feature maps generated by the feature map extraction unit.

Abstract: An apparatus for detecting an object of a vehicle is provided. The apparatus includes a camera that acquires an image from front of a vehicle and a controller that generates feature pyramid images based on a plurality of feature images extracted from the image. The controller also generates feature aggregation images by filtering the feature pyramid images, detects a pedestrian area from the feature aggregation images, and detects face regions from the feature pyramid images. At least one of the face regions that overlaps the pedestrian area is then determined as a face of a pedestrian.

Abstract: Disclosed a normalized metadata generation device, and object occlusion detection device and method. A normalized metadata generation method includes generating a multi-ellipsoid based three-dimensional human model using perspective features of a plurality of two-dimensional images obtained by the multiple cameras, performing scene calibration based on the three-dimensional human model to normalize object information of the object included in the two-dimensional images, and generating normalized metadata of the object from the two-dimensional images on which the scene calibration is performed.

Abstract: The apparatus for removing haze from an image using a fuzzy membership function includes memory configured to store computer-readable instructions; and a processor configured to execute the instructions, wherein the processor calculates a hazy value and a transmission map using an input image including a hazy component and generates a restored image from which the hazy component has been removed using the hazy value and the transmission map, and wherein the processor selects a first area in the input image, calculates a fuzzy membership function of pixels of the input image with respect to the hazy value using brightness values of the pixels of the input image and brightness values of pixels of the first area, and calculates the transmission map using the brightness values of pixels of the first area and the fuzzy membership function.

Abstract: An apparatus for detecting an object of a vehicle is provided. The apparatus includes a camera that acquires an image from front of a vehicle and a controller that generates feature pyramid images based on a plurality of feature images extracted from the image. The controller also generates feature aggregation images by filtering the feature pyramid images, detects a pedestrian area from the feature aggregation images, and detects face regions from the feature pyramid images. At least one of the face regions that overlaps the pedestrian area is then determined as a face of a pedestrian.

Abstract: Disclosed a normalized metadata generation device, and object occlusion detection device and method. A normalized metadata generation method includes generating a multi-ellipsoid based three-dimensional human model using perspective features of a plurality of two-dimensional images obtained by the multiple cameras, performing scene calibration based on the three-dimensional human model to normalize object information of the object included in the two-dimensional images, and generating normalized metadata of the object from the two-dimensional images on which the scene calibration is performed.

Abstract: The apparatus for removing haze from an image using a fuzzy membership function includes memory configured to store computer-readable instructions; and a processor configured to execute the instructions, wherein the processor calculates a hazy value and a transmission map using an input image including a hazy component and generates a restored image from which the hazy component has been removed using the hazy value and the transmission map, and wherein the processor selects a first area in the input image, calculates a fuzzy membership function of pixels of the input image with respect to the hazy value using brightness values of the pixels of the input image and brightness values of pixels of the first area, and calculates the transmission map using the brightness values of pixels of the first area and the fuzzy membership function.

Abstract: Provided is an image sensor. The image sensor includes a pixel array including a plurality of pixel blocks. Each of the plurality of pixel blocks includes a plurality of pixels arranged in a matrix form. Each of the plurality of pixels includes a plurality of phase difference sensing pixels. Each of the plurality of phase difference sensing pixels may be periodically repeatedly arranged in the pixel array in a horizontal direction and a vertical direction.

Abstract: A lens distortion correction device and an application processor having the same include a distortion correction unit configured to correct a distorted image into an undistorted image and an image enhancement unit configured to improve the undistorted image using a high-frequency component of the distorted image.

Abstract: Disclosed are an apparatus and a method for detecting an object automatically and estimating depth information of an image captured by an imaging device having a multiple color-filter aperture. A background generation unit detects a movement from a current image frame among a plurality of continuous image frames captured by an MCA camera to generate a background image frame corresponding to the current image frame. An object detection unit detects an object region included in the current image frame based on differentiation between a plurality of color channels of the current image frame and a plurality of color channels of the background image frame. According to an embodiment of the present invention, it is possible to automatically detect an object by a repetitively updated background image frame and to accurately estimate object information by separately detecting an object for each color channel by considering a property of the MCA camera.

Abstract: The present invention relates to an auto-focus system and method based on a sensor, using hierarchical extraction and motion estimation for an image. The auto-focus method may include the steps of: (a) extracting a phase difference image from a sensed image; (b) extracting a robust feature image which satisfies a preset reference with respect to noise and out-of-focus blur, from the phase difference image; and (C) estimating a motion vector for lens shift from the feature image.

Abstract: An apparatus for detecting multiple objects using adaptive block partitioning is disclosed. An object contour extracting unit configured to extract a contour information of an object using a local binary pattern LBP and difference image between adjacent images. An adaptive block partitioning unit configured to perform a block partitioning of an object not overlapped based on the extracted contour information. A motion quantization unit configured to calculate a motion orientation histogram MOH of the object by performing N-directional quantization about a motion vector. An object detection unit configured to detect the object using a block of the partitioned object, the contour information and the MOH, and estimate a moving direction of the object after performing labeling the detected object.

Abstract: A method and an apparatus for restoring a motion blurred image are disclosed. The method of restoring a motion blurred image comprises calculating a motion trajectory and a project trajectory of a camera using an embedded sensor; estimating a point spread function according to camera motion by using the motion trajectory and the project trajectory; and restoring the motion blurred image using the estimated point spread function and a spatially variant activity map.

Abstract: Provided is an image sensor. The image sensor includes a pixel array including a plurality of pixel blocks. Each of the plurality of pixel blocks includes a plurality of pixels arranged in a matrix form. Each of the plurality of pixels includes a plurality of phase difference sensing pixels. Each of the plurality of phase difference sensing pixels may be periodically repeatedly arranged in the pixel array in a horizontal direction and a vertical direction.

Abstract: Provided are a non-dyadic lens distortion correction method and an apparatus thereof. The non-dyadic lens distortion correction method includes: (a) acquiring a non-dyadic lens image photographed through a non-dyadic lens; (b) correcting geometric distortion for the non-dyadic lens image by stage by applying a magnification ratio based on a projection model; and (c) compensating a high-frequency component of an image corrected in a previous step by the patch unit in the non-dyadic lens image of which the geometric distortion is corrected.

Abstract: The present invention relates to an auto-focus system and method based on a sensor, using hierarchical extraction and motion estimation for an image. The auto-focus method may include the steps of: (a) extracting a phase difference image from a sensed image; (b) extracting a robust feature image which satisfies a preset reference with respect to noise and out-of-focus blur, from the phase difference image; and (C) estimating a motion vector for lens shift from the feature image.

Abstract: A lens distortion correction device and an application processor having the same include a distortion correction unit configured to correct a distorted image into an undistorted image and an image enhancement unit configured to improve the undistorted image using a high-frequency component of the distorted image.

Abstract: A lens distortion correction device and an application processor having the same include a distortion correction unit configured to correct a distorted image into an undistorted image and an image enhancement unit configured to improve the undistorted image using a high-frequency component of the distorted image.

Abstract: A method and an apparatus for restoring a motion blurred image are disclosed. The method of restoring a motion blurred image comprises calculating a motion trajectory and a project trajectory of a camera using an embedded sensor; estimating a point spread function according to camera motion by using the motion trajectory and the project trajectory; and restoring the motion blurred image using the estimated point spread function and a spatially variant activity map.