摘要:
There is provided an image processing device including: a data storage unit that stores object identification data for identifying an object operable by a user and feature data indicating a feature of appearance of each object; an environment map storage unit that stores an environment map representing a position of one or more objects existing in a real space and generated based on an input image obtained by imaging the real space using an imaging device and the feature data stored in the data storage unit; and a selecting unit that selects at least one object recognized as being operable based on the object identification data, out of the objects included in the environment map stored in the environment map storage unit, as a candidate object being a possible operation target by a user.
摘要:
A motion-setting section (61) sets a motion amount and a motion direction for obtaining processing coefficients. A student-image-generating section (62) generates student images obtained by adding a motion blur to a teacher image not only based on the set motion amount and the set motion direction but also by changing at least one of the motion amount and motion direction in a specific ratio and student images obtained by adding no motion blur to the teacher image. A prediction-tap-extracting section (64) extracts, in order to extract a main term that mainly contains component of the target pixel, at least a pixel value of pixel in the student image whose space position roughly agrees with space position of the target pixel in the teacher image. A processing-coefficient-generating section (65) generates processing coefficients for predicting the target pixels in the teacher images from the pixel values of extracted pixels based on a relationship between the pixels thus extracted and the target pixels in the teacher images. The processing coefficients that are suitable for any motion blur removing which is robust against any shift of the motion vector can be generated through learning.
摘要:
There is provided an image processing device, including: a data storage unit storing feature data indicating a feature of appearance of an object; an environment map generating unit for generating an environment map representing a position of one or more objects existing in a real space based on an input image obtained by imaging the real space using an imaging device and the feature data stored in the data storage unit; and an output image generating unit for generating an output image obtained by erasing an erasing target object from the input image based on a position of the erasing target object specified out of objects present in the input image represented in the environment map and a position of the imaging device.
摘要:
An image processing apparatus includes a storage unit in which regression coefficient data is stored for each class on the basis of a tap in which a linear feature amount corresponding to a pixel of interest of first image data and a non-linear feature amount determined from the image data are used as elements; a classification unit configured to classify each of linear feature amounts of a plurality of items of input data of the input first image into a predetermined class; a reading unit configured to read the regression coefficient data; and a data generation unit configured to generate data of a second image obtained by making the first image have higher quality by performing a product-sum computation process by using the regression coefficient data read from the reading unit and elements of the tap of each of the plurality of items of input data of the input first image.
摘要:
A motion-vector detector determines the centroid of pixels on a reference frame that is identified with position information set in a database and associated with a feature address corresponding to a feature of a target pixel. The motion-vector detector detects, as a motion vector of the target pixel, a vector that has a starting point at a pixel on the reference frame which corresponds to the target pixel on a current frame and has an end point at the determined centroid. The present invention can be applied to an apparatus for generating a motion vector and allows prompt detection of a motion vector.
摘要:
A target-pixel-setting section (31) sets a target pixel in a target image to be predicted. A motion-direction-detecting section (32) detects a motion direction corresponding to the target pixel. A pixel-value-extracting section (36) extracts from peripheral images corresponding to the target image, in order to extract a main term that mainly contains component of the target pixel in a moving object that encounters a motion blur in the peripheral images, at least pixel values of pixels in the peripheral images whose space position roughly agree with space position of the target pixel. A processing-coefficient-setting section (37a) sets a specific motion-blur-removing-processing coefficient. A pixel-value-generating section (38a) newly generates pixel values for processing from the pixel values extracted by the pixel-value-extracting section (36) corresponding to the motion direction and generates pixel values corresponding to the target pixel based on the pixel values for processing and the specific motion-blur-removing-processing coefficients. It is possible to perform a robust motion-blur-removing processing on any shifts of motion vector.
摘要:
An image processing apparatus includes a storage unit in which regression coefficient data is stored for each class on the basis of a tap in which a linear feature amount corresponding to a pixel of interest of first image data and a non-linear feature amount determined from the image data are used as elements; a classification unit configured to classify each of linear feature amounts of a plurality of items of input data of the input first image into a predetermined class; a reading unit configured to read the regression coefficient data; and a data generation unit configured to generate data of a second image obtained by making the first image have higher quality by performing a product-sum computation process by using the regression coefficient data read from the reading unit and elements of the tap of each of the plurality of items of input data of the input first image.
摘要:
An image processing device for converting an input image into an output image whose blur is reduced more, the image processing device including: first image extracting section configured to extract a plurality of pixels composed of a pixel of the input image which pixel corresponds to a pixel of interest as a pixel to which to direct attention within the output image and predetermined pixels surrounding the pixel of the input image; first feature quantity calculating configured to calculate a first feature quantity from the plurality of pixels extracted by the first image extracting section; processing coefficient generating section; second pixel extracting section configured to extract a plurality of pixels composed of the pixel corresponding to the pixel of interest and predetermined pixels surrounding the pixel corresponding to the pixel of interest from the input image; and predicting section.
摘要:
A motion-vector detector determines the centroid of pixels on a reference frame that is identified with position information set in a database and associated with a feature address corresponding to a feature of a target pixel. The motion-vector detector detects, as a motion vector of the target pixel, a vector that has a starting point at a pixel on the reference frame which corresponds to the target pixel on a current frame and has an end point at the determined centroid. The present invention can be applied to an apparatus for generating a motion vector and allows prompt detection of a motion vector.
摘要:
A coefficient learning apparatus includes a regression coefficient calculation unit configured to obtain a tap from an image of a first signal; a regression prediction value calculation unit configured to perform a regression prediction computation; a discrimination information assigning unit configured to assign discrimination information to the pixel of interest; a discrimination coefficient calculation unit configured to obtain a tap from the image of the first signal; a discrimination prediction value calculation unit configured to perform a discrimination prediction computation; and a classification unit configured to classify each of the pixels of the image of the first signal into one of the first discrimination class and the second discrimination class. The regression coefficient calculation unit further calculates the regression coefficient using only the pixels classified as the first discrimination class and further calculates the regression coefficient using only the pixel classified as the second discrimination class.