Abstract: Systems and methods to recognize a parking space are disclosed. One or more images are captured using one or more cameras coupled to a vehicle at a parking space. Data associated with the parking space are determined from the one or more images. The data associated with the parking space are compared to data stored in a storage device. A parking condition for the vehicle is determined based on the comparing.

Abstract: An optical detecting device with a tracking function includes an image acquiring module and a processor. The image acquiring module is grouped into a first cluster and a second cluster of pixels. The first cluster and the second cluster are arranged adjacent to each other, and used to respectively acquire a first imaging result and a second imaging result both containing an indicating mark. The processor is electrically connected to the image acquiring module and adapted to track a proceeding direction of the indicating mark by computing difference between the first imaging result and the second imaging result. The optical detecting device further includes a memory module electrically connected to the processor, and the processor analyzes the computed difference via a lookup table stored inside the memory module to determine the proceeding direction.

Abstract: A reliability calculation apparatus calculates a reliability of a recognized object that is recognized as being present on a route on which a vehicle travels. The reliability of the recognized object is used for driving control of the vehicle. In the reliability calculation apparatus, a provisional reliability calculating unit determines a feature quantity of each of a plurality of recognized objects, selects a plurality of pairs of recognized objects from the plurality of recognized objects, determines a difference in feature quantity of each pair of recognized objects, and calculates a reliability that decreases as the difference in feature quantity increases as a provisional reliability of each pair of recognized objects. An integrated reliability calculating unit calculates an integrated reliability of each recognized object from the provisional reliabilities of the plurality of pairs of recognized objects.

Abstract: A system and method for determining egomotion can include determining correspondence maps between pairs of images of an odometry set; identifying odometry features shared between the images of the odometry set; and determining the egomotion based on the odometry features.

Abstract: A method for reproducing frames in an electronic device may include detecting at least one animation region selected from a plurality of animation regions, determining a plurality of random sequences for the at least one selected animation region, generating an output sequence by applying weights to the determined random sequences, and reproducing the generated output sequence.

Abstract: A method and an associated device for detecting fraud during automatic face recognition, the method comprising the following steps: acquiring a first image of the face by means of a first sensor having a first field angle, and a second image of the face by means of a second sensor having a second field angle that is narrower than the first field angle; analyzing the first image to verify that there is no frame around the face; and analyzing the second image to verify that there is no moiré effect.

Abstract: A Region Merging image segmentation algorithm based on boundary extraction is disclosed, comprising the steps of calculating a gradient image, extracting a boundary and carrying out initial segmentation and Region Merging, wherein each pixel is regarded as one region when initial segmentation is not conducted. In the Region Merging process, the portion of the common boundary of two adjacent regions that lies on the boundary image is taken as the merging cost, the regions are merged according to the ascending order of the mean gradient value inside the region, and a texture difference evaluation mechanism is introduced to reduce the wrong segmentation. The algorithm solves the problems of the other current segmentation algorithms, such as over-segmentation, easy to be influenced by noise and illumination, large in computation and memory consumption, in need of a large number of samples being marked manually and the like.

Abstract: A system and method for method for identifying key points in a multimedia data element (MMDE). The method includes: identifying, via a computer vision system, a plurality of candidate key points in the MMDE, wherein a size of each candidate key point is equal to a predetermined size, wherein a scale of each candidate key point is equal to a predetermined scale; analyzing the plurality of candidate key points to determine a set of properties for each candidate key point; comparing the sets of properties of the plurality of candidate key points; and selecting, based on the comparison, a plurality of key points from among the candidate key points.

Abstract: A decoding method is disclosed that comprises:—decoding (S120) a stream to obtain a decoded standard dynamic range picture and colour metadata associated with the standard dynamic range picture, wherein the colour metadata are representative at least of characteristics of a high dynamic range picture associated with the standard dynamic range picture; and—reconstructing (S130) a high dynamic range access the input stream(s) picture from the decoded standard dynamic range picture and from the colour metadata.

Abstract: Provided herein are a display device and an image processing method thereof. The display device includes an image processor processing original image data including color coordinate values for R, G, and B components in an RGB color space, and output processed original image data as corrected image data, and a display unit outputting an image corresponding to the corrected image data, wherein the image processor sets a corrected color coordinate value for an arbitrary component of the R, G, and B components based on a type of the image, sets corrected color coordinate values for remaining components in accordance with the corrected color coordinate value for the arbitrary component, and generates the corrected image data based on the corrected color coordinate values for the arbitrary component and the remaining components.

Abstract: An image processing method includes obtaining a difference map of an original image, obtaining an edge feature parameter of a first pixel in an intermediate image based on a pixel value of a pixel in the difference map, obtaining an edge feature parameter of a second pixel in a target image based on the edge feature parameter, and obtaining the target image based on the edge feature parameter of the second pixel.

Abstract: An approach is provided for determining the quality of camera pose data. The approach, for example, involves identifying camera pose data for a camera used to capture an image. The approach further involves processing the image to determine a pixel location of features visible in the image, wherein each feature has a known physical location (e.g., obtained using survey techniques or equivalent). The approach further involves determining a camera physical location of the camera based on the camera pose data. The approach further involves determining an physical location of the image plane based on the camera pose data and/or camera parameters (e.g., intrinsic camera parameters). The approach further involves projecting a ray from the camera physical location thorough the image plane physical location corresponding to the pixel location determined for each feature, and computing a minimum distance between the projected ray and the known physical location of each feature.

Abstract: A method relating to image compression includes acquiring image data of an image, wherein the image includes a matrix of pixels, and the image data include pixel values of the matrix of pixels. The method also includes generating, based on the image data, a first-level data set including pixel values of a portion of the matrix of pixels. The method further includes determining at least one coding mode for the first-level data set, encoding the first-level data set into a code stream based on the at least one coding mode, and packaging the code stream into a modified code stream.

Abstract: [Object] To provide an information processing system, a storage medium, and an information processing method that can make a response to a user on the basis of an episode constructed from an interaction with the user to enhance the user's memory.

Abstract: A method for magnetic resonance imaging (MRI) includes performing an echo planar imaging acquisition using inverted up/down phase encoding directions and reconstructing acquired images having geometric distortions along the phase encoding directions due to off-resonant spins; feed-forward estimating by a convolutional neural network (CNN) a phase distortion map from the acquired images; where the CNN is trained to minimize a similarity metric between un-warped up/down image pairs; and performing geometric distortion correction of the acquired images using the phase distortion map to unwarp the acquired images.

Abstract: An information-processing apparatus includes: a first acquisition unit configured to acquire gradation characteristic information which relates to a gradation characteristic; a second acquisition unit configured to acquire axial characteristic information which relates to an axial characteristic including a distribution, on an axis, of graduations corresponding to brightness-related values related to brightness of input image data; and a generation unit configured to generate, based on the input image data, the gradation characteristic information, and the axial characteristic information, distribution information indicating a distribution of the brightness-related value of the input image data using the axis according to the axial characteristic information.

Abstract: The disclosed apparatus, systems and methods relate to a framelet-based iterative algorithm for polychromatic CT which can reconstruct two components using a single scan. The algorithm can have various steps including a scaled-gradient descent step of constant or variant step sizes; a non-negativity step; a soft thresholding step; and a color reconstruction step.

Abstract: A refined segmentation system, method and device of an image shadow area are provided. The system of the present invention includes: a feature extraction network, a reverse fusion network, and a weighted fusion network. The feature extraction network includes a plurality of sampling layers which are arranged sequentially, a plurality of segmentation features of the shadow areas in the input images are obtained through the sampling layers sequentially. The reverse fusion network includes a plurality of layered reverse fusion branches, each of which includes a plurality of feature fusion layers arranged in sequence, and two input features are fused in sequence through each feature fusion layer. The weighted fusion network is configured to perform weighted fusion on outputs of the plurality of reverse fusion branches to obtain a final segmentation result of the shadow area of the input image.

Abstract: Some implementations may include a method for watermarking an identification document, the method including: modulating a spatial luminance pattern associated with a first digital watermark to encode a first portion of personally identifiable information; modulating a spatial chrominance distribution associated with a second digital watermark to encode a second portion of the personally identifiable information; and applying the first digital watermark and the second digital watermark to the identification document.

Abstract: An electronic device and a method of operating the electronic device are provided. The electronic device includes a proximity detector; an iris recognition module; a memory; and a processor electrically connected to the proximity detector, the iris recognition module, and the memory, wherein the processor is configured to execute an iris recognition operation based on the iris recognition module; determine proximity of an object based on the proximity detector while the iris recognition operation is performed; and, if the proximity of the object includes within a set reference range, stop the iris recognition operation.