Abstract:
An apparatus and method for parsing a human body image may be implemented by acquiring a depth image including a human body, and detecting a plurality of points in the acquired depth image by conducting a minimum energy skeleton scan on the depth image.
Abstract:
A method and apparatus for processing a depth image determines a number of mods (NoM) for corresponding pixels in a plurality of depth images. The corresponding pixels may represent a same three-dimensional (3D) point. The NoM may be determined to be a value for minimizing a Markov random field (MRF) energy. A depth value for one depth image may be recovered, and a depth value for another depth image may be updated using the recovered depth value.
Abstract:
Provided is a stereo matching method and apparatus. A stereo matching apparatus may generate a disparity map by transforming a disparity map of a previous frame based on determined motion information of a camera between the previous frame and the current frame, calculate a confidence for the generated disparity map, and adjust a disparity map corresponding to the current frame based on the confidence and the generated disparity map.
Abstract:
Provided is an image processing apparatus and method for detecting a transparent image from an input image. The image processing apparatus may include an image segmenting unit to segment an input image into a plurality of segments, a likelihood determining unit to determine a likelihood that a transparent object is present between adjacent segments among the plurality of segments, and an object detecting unit to detect the transparent object from the input image based on the likelihood.
Abstract:
An image processing apparatus is provided. The image processing apparatus determines whether a first charge quantity of charges stored in a first charge storage is greater than or equal to a predetermined saturation level, the first charge storage among a plurality of charge storages configured to store charges generated by a sensor of a depth camera. According to the determination result, when the first charge quantity is greater than or equal to the saturation level, the image processing apparatus may calculate the first charge quantity from at least one second charge quantity of charges stored in at least one second charge storage which is different from the first charge storage among the plurality of charge storages.
Abstract:
Provided is an image processing apparatus and method for detecting a transparent image from an input image. The image processing apparatus may include an image segmenting unit to segment an input image into a plurality of segments, a likelihood determining unit to determine a likelihood that a transparent object is present between adjacent segments among the plurality of segments, and an object detecting unit to detect the transparent object from the input image based on the likelihood.
Abstract:
A method and apparatus for processing a depth image determines a number of mods (NoM) for corresponding pixels in a plurality of depth images. The corresponding pixels may represent a same three-dimensional (3D) point. The NoM may be determined to be a value for minimizing a Markov random field (MRF) energy. A depth value for one depth image may be recovered, and a depth value for another depth image may be updated using the recovered depth value.
Abstract:
A method and apparatus for processing a depth image that removes noise of a depth image may include a noise estimating unit to estimate noise of a depth image using an amplitude image, a super-pixel generating unit to generate a planar super-pixel based on depth information of the depth image and the noise estimated, and a noise removing unit to remove noise of the depth image using depth information of the depth image and depth information of the super-pixel.
Abstract:
Provided is a method and apparatus for modeling a human body using a depth image and a color image. An image processing apparatus may extract a body area from a color image based on a depth value of a depth image, may match a boundary of the extracted body area and a boundary of a generic body mesh model, and may deform a mesh of the generic body mesh model based on a depth value of a pixel positioned within the boundary of the extracted body area.