Abstract: There is provided with an image processing apparatus for extracting an object region from an image. An image acquisition unit acquires an image. A designation acquisition unit acquires designation of one or more extraction colors that belong to the object region of the image and designation of one or more non-extraction colors that do not belong to the object region of the image. A derivation unit derives a color conversion parameter, based on the extraction color and the non-extraction color. A conversion unit converts a color of the image based on the color conversion parameter. An extraction unit extracts the object region from the image, based on the image and the extraction color after the conversion.

Abstract: The various embodiments of the present disclosure are directed towards methods for tone mapping High-Dynamic-Range (HDR) image data, as well as controlling the brightness of the image encoded by HDR the image data and/or the tone-mapped image data. HDR image is captured. A tone mapping function for the HDR image data is generated. To generate the tone mapping function, control points are dynamically determined based on an analysis of the HDR image data. The tone mapping function is fit to the control points. The tone mapping function is a non-linear function, and is described by a curve in a plane. The shape of the curve is constrained by a line generated from a portion of the control points. The tone mapping function is applied to the HDR image data. A color-compression is applied to the tone mapped image data to generate Standard Dynamic Range or Low Dynamic Range image data.

Abstract: Methods and apparatus for image processing are provided. The method comprises receiving input of a visible-ray image and a far-infrared-ray image obtained by photographing a same subject, estimating a blur estimation result in the visible-ray image, wherein estimating a blur estimation result comprises calculating a correlation between the visible-ray image and each of a plurality of filter-applied far-infrared ray images in which a different filter is applied to the far-infrared-ray image and selecting the filter for which the calculated correlation is highest, and performing a correction process on the visible-ray image based, at least in part, on the blur estimation result to generate a corrected visible-ray image from which the blur is reduced, wherein generating the corrected visible-ray image comprises applying, to the visible ray image, an inverse filter having an inverse characteristic to a characteristic of the selected filter.

Abstract: An image processing method including acquiring depth information on at least one of a first portion of a specific object included in a target image or a second portion in a region of the target image that excludes the specific object based on reference pattern information, the reference pattern information including first information on a shape of an object included in an image and second information on a relative position between at least two objects included in the image, and applying a dynamic effect to at least one of the first portion or the second portion based on the acquired depth information may be provided.

Abstract: In example implementations, a method is provided. The method may be executed by a processor. The method includes receiving an image. A person from a plurality of people within the image is identified. The person is segmented from the image. A background image of the image is replaced with a clean background image to remove the plurality of people from the image except the person that is identified.

Abstract: Systems, methods, and devices are provided for detecting coordinate information about a screen display shown at a monitor unit. The monitor unit is located within the field of view of a vision-based computing device. A set of source images captured by the camera representative of the screen display shown at the monitor unit are stored. A neural network model is stored in memory. A processor is configured to preprocess the set of source images to obtain an input frame and to process the input frame with the loaded neural network model to predict corner coordinates of the screen display in real-time. In a further feature, the processor may be configured to estimate a pose of the vision-based computing device relative to the monitor unit when a level of confidence in the updated corner coordinates exceeds a threshold.

Abstract: Images can be edited to include features similar to a different target image. An unconditional generative adversarial network (GAN) is employed to edit features of an initial image based on a constraint determined from a target image. The constraint used by the GAN is determined from keypoints or segmentation masks of the target image, and edits are made to features of the initial image based on keypoints or segmentation masks of the initial image corresponding to those of the constraint from the target image. The GAN modifies the initial image based on a loss function having a variable for the constraint. The result of this optimization process is a modified initial image having features similar to the target image subject to the constraint determined from the identified keypoints or segmentation masks.

Abstract: A method of localization for a non-transitory computer readable storage medium storing one or more programs is disclosed. The one or more programs comprise instructions, which when executed by a computing device, cause the computing device to perform by one or more autonomous vehicle driving modules execution of processing of images from a camera and data from a LiDAR using the following steps comprising: computing, in response to features from a 3D submap and features from a global map, matching score between corresponding features of a same class between the 3D submap and the global map; selecting, for each feature in the 3D submap, a corresponding feature with the highest matching score from the global map; determining a feature correspondence to be invalid if a distance between corresponding features is larger than a threshold; and removing the invalid feature correspondence.

Abstract: Method for treating a surface includes: automatically evaluating at least one digital image which includes the target surface; determining the nature of the target surface according to the evaluation of the at least one digital image; determining at least one available treatment implement according to the evaluation of the at least one image; determining the nature of the surface treatment according to the evaluation of the at least one image; automatically determining a use of the determined treatment implement in the determined treatment of the determined surface; and providing information analogous to the determined use of the treatment implement.

Abstract: Embodiments for implementing intelligent classification of region of interest in an organism in a computing environment by a processor. Time series data of a contrast agent in one or more regions of interest captured from multispectral image streams may be collected. The one or more regions of interest may be classified into one of a plurality of classes by applying one or more perfusion models, representing spatio-temporal behavior of the contrast agent reflected by the time series data, and by using a machine learning operation.

Abstract: There is provided a computer-implemented method (200) for obscuring one or more facial features of a subject in an image. A head of the subject is detected in the image (202) and a location of one or more facial features of the subject is identified in the image (204). A region of the image to modify is determined based on the location of the one or more facial features (206). The determined region comprises a part of the head on which the one or more facial features are located. The image within the determined region is modified to obscure the one or more facial features (208).

Abstract: To provide an image processing device which is user-friendly and is able to acquire an optimum image in which a user's intention is reflected based on various kinds of parameter setting by the user, the image processing device includes: a combination processing unit configured to combine a visible-light image signal and an infrared-light image signal to generate a combined image signal, and a parameter setting unit configured to set a parameter other than combination ratios of the visible-light image signal and the infrared-light image signal in the combined image signal. The combination processing unit changes the combination ratio in accordance with a change in the parameter when the parameter setting unit changes the parameter.

Abstract: A method for image processing, an electronic device, and a non-transitory computer readable medium are disclosed. The method includes obtaining an image in a chrominance-luminance separated color mode; traversing luminance components of all pixels in the image to determine a number of pixels corresponding to the respective luminance component; generating an original luminance distribution of the image based on the luminance components and the number of the pixels corresponding to the respective luminance component; generating a luminance mapping relationship between a preset standard luminance distribution and the original luminance distribution; and adjusting the luminance components of the pixels in the image based on the luminance mapping relationship to obtain a processed image.

Abstract: The present disclosure provides a method for video processing. The method includes: obtaining a current image frame and a previous image frame in a video to be processed based on a preset sampling frequency value; obtaining a first skin tone weight map of the current image frame and a second skin tone weight map of the previous image frame; superimposing the first skin tone weight map and the second skin tone weight map to obtain a third skin tone weight map; and superimposing a first luminance map of the current image frame and a second luminance map based on the third skin tone weight map to obtain a second image. The first luminance map is a luminance map of the current image frame, and the second luminance map is a map obtained after the first luminance map is smoothed.

Abstract: A live facial recognition method includes capturing a plurality of images of a face of a subject under recognition; obtaining time-varying data according to the images, the time-varying data representing a periodic variation of facial color of the subject under recognition due to facial vasoconstriction and vasodilation caused by heartbeat; and comparing the time-varying data with a predetermined frequency range. The subject under recognition is determined to be a living subject when the time-varying data is within the predetermined frequency range.

Abstract: Method and systems for image deblurring in a vehicle. The methods and systems include determining a point spread function based on vehicle motion data and a depth map received from vehicle motion sensors and a depth sensor. A deblur matrix is calculated based on the point spread function. A blurred input image, received from an imaging device, is deblurred based on the deblur matrix to thereby provide a deblurred output image. A function of the vehicle is controlled based on the deblurred output image.

Abstract: Systems and methods for providing panoramic image and/or video content using spatially selective encoding and/or decoding. Panoramic content may include stitched spherical (360-degree) images and/or VR video. In some implementations, selective encoding functionality may be embodied in a spherical image capture device that may include two lenses configured to capture pairs of hemispherical images. Encoded source images may be decoded and stitched in order to obtain a combined image characterized by a greater field of view as compared to source images. The stitched image may be encoded using a selective encoding methodology including: partitioning a stitched image into multiple portions, determining if a portion is to be re-encoded. If the image portion is to be re-encoded, re-encoding the image portion. If an image portion is not to be re-encoded, copying previously encoded image portion in lieu of encoding.

Abstract: Among other things, an imaging sensor includes a two-dimensional array of photosensitive elements and a surface to receive a sample within a near-field distance of the photosensitive elements. Electronics classify microbeads in the sample as belonging to different classes based on the effects of different absorption spectra of the different classes of microbeads on light received at the surface. In some examples, the number of different distinguishable classes of microbeads can be very large based on combinations of the effects on light received at the surface of the different absorption spectra together, spatial arrangements of colorants in the microbeads that impart the different absorption spectra, different sizes of microbeads, and different shapes of microbeads, among other things.

Abstract: An imaging apparatus includes a circuitry configured to perform depth analysis of a scene by time-of-flight imaging and to perform motion analysis in the scene by structured light imaging, wherein identical sensor data is used for both, the depth analysis and the motion analysis.

Abstract: For searching virtual content information, a processor searches the virtual content information including a virtual object contour. The processor further retrieves an image based on the virtual content information.