Abstract: A method for enhancing image resolution includes obtaining one or more images of a scene. The one or more images are associated with a first depth map. The method further includes determining a second depth map of the scene based upon the one or more images. The second depth map has a higher resolution than the first depth map.

Abstract: Described are methods for identifying the in-field positions of plant features on a plant by plant basis. These positions are determined based on images captured as a vehicle (e.g., tractor, sprayer, etc.) including one or more cameras travels through the field along a row of crops. The in-field positions of the plant features are useful for a variety of purposes including, for example, generating three-dimensional data models of plants growing in the field, assessing plant growth and phenotypic features, determining what kinds of treatments to apply including both where to apply the treatments and how much, determining whether to remove weeds or other undesirable plants, and so on.

Abstract: Some implementations provide a machine-assisted method for screening a person, the method including: receiving, at a scanning device, an identification document presented by the person, the identification document showing a machine-readable code that encodes personally identifiable information of the person, a biometric of the person, and printed information; scanning the machine-readable code on the identification document to extract personally identifiable information of the person; comparing the extracted personally identifiable information against records stored at a database; determining that the extracted personal identifiable information matches a record stored at the database; receiving data encoding the biometric of the person on the identification document for comparison with the person presenting the identification document; receiving a determination that the biometric from the identification document identifies the person presenting the identification document; and determining whether the identifi

Abstract: A method for adapting a matching model of an object comprising the step of providing an electronic image of the object; providing a matching model of the object, the matching model consisting of a plurality of points; determining a pose of the object in said electronic image by using a matching approach that uses said matching model; transforming the matching model according to said pose, yielding a transformed model; determining for at least one point of said transformed model a corresponding point in said electronic image; and adapting the matching model according to the at least one determined corresponding point.

Abstract: A computer aided diagnostic system and automated method to classify a kidney. Image data for a medical scan that includes image data of a kidney may be received. The kidney image data may be segmented from other image data of the medical scan. One or more iso-contours may be registered for the kidney image data, and renal cortex image data may be segmented from the kidney image data based on the one or more registered iso-contours. The kidney may be classified by analyzing one or more features determined from the segmented renal cortex image data using a learned model associated with the one or more features.

Abstract: Methods and apparatus are disclosed for reducing an amount of fixed pattern noise from sequential frames captured by IR imaging sensor(s) that contain known continuous motion component(s). Improved scene based non-uniformity correction techniques are employed for recursively updated set of pixel correction terms for each frame, in order to generate corrected frames. The set of pixel correction terms may be recursively updated through a multi-step process making use of the known continuous motion component, which may comprise a dithered signal.

Abstract: A vehicle includes a camera capturing an image of a road sign associated with a road that the vehicle is traveling on. A first processing device is communicatively coupled to the camera and recognizes text characters in the captured image. A second processing device is communicatively coupled to the first processing device and converts the recognized text characters into an electronic speech signal. A loudspeaker is communicatively coupled to the second processing device and converts the electronic speech signal into audible speech that can be heard by the driver of the vehicle.

Abstract: An image-feature-value calculating unit extracts an image feature value of an image of a cell candidate area. An NRBC discriminating unit uses a pre-trained discriminator to identify whether or not a target cell is shown in the cell candidate area, on the basis of the image feature value of the image of the cell candidate area. When the cell candidate area is identified as an area in which a target cell is shown, a discrimination result display unit displays the image of the cell candidate area. When the cell candidate area is identified as an area in which a target cell is shown, a discriminator training unit trains the discriminator by using the image feature value of the image of the cell candidate area as a training sample on the basis of a user input about whether or not a target cell is shown in the cell candidate area.

Abstract: An object detection method includes an image acquisition step of acquiring an image including a target object, a layer image generation step of generating a plurality of layer images by one or both of enlarging and reducing the image at a plurality of different scales, a first detection step of detecting a region of at least a part of the target object as a first detected region from each of the layer images, a selection step of selecting at least one of the layer images based on the detected first detected region and learning data learned in advance, a second detection step of detecting a region of at least a part of the target object in the selected layer image as a second detected region, and an integration step of integrating a detection result detected in the first detection step and a detection result detected in the second detection step.

Abstract: A subject's head position and motion can be tracked by analyzing a series of frames from a monocular camera and mapping distinguishing points visible in the frames onto an elliptical cylinder. The tracking data can be used to control a physical pan/tilt actuator or to reconfigure/reposition virtual objects, images of which can be synthesized and displayed, or composited back into the original frames and displayed.

Abstract: A method for ensemble based labeling is provided. The method includes obtaining a plurality of samples of an object. The method further includes estimating, for each of the plurality of samples, a probability that a label applies to the sample, for each of a plurality of labels. The method also includes determining a candidate label among the plurality of labels, based on the estimated probabilities of the plurality of samples for each of the plurality of labels. The method further includes calculating a dispersion of the estimated probabilities of the plurality of samples for the candidate label; and identifying a target label among the plurality of labels, based on the estimated probabilities of the plurality of samples for the candidate label, the dispersion for the candidate label, and a number of the plurality of samples.

Abstract: A control apparatus is configured to execute: acquisition processing of acquiring, from at least one data acquisition apparatus, as data on a second object, time series data on a series of pieces of information on the second object that has been collected since the at least one data acquisition apparatus detected the second object; determination processing of determining whether or not the first and the second object are identical to each other based on information on the first and the second object; and storage processing of storing, when the determination processing results that the first and the second object are/aren't identical to each other, the data on the second object and the data on the first object in association with/without each other, and when the determination processing results in a determination that the first object and the second object are not identical to each other.

Abstract: An improved system and method for digital image classification is provided. A host computer having a processor is coupled to a memory storing thereon reference feature data. A graphics processing unit (GPU) having a processor is coupled to the host computer and is configured to obtain, from the host computer, feature data corresponding to the digital image; to access, from the memory, the one or more reference feature data; and to determine a semi-metric distance based on a Poisson-Binomial distribution between the feature data and the one or more reference feature data. The host computer is configured to classify the digital image using the determined semi-metric distance.

Abstract: Systems and methods for detecting motion in compressed video are provided. Some methods can include parsing a stream of compressed video, obtaining macroblock size information from the parsed stream, computing factors derived from the macroblock size information, computing adaptive threshold values derived from relative frame characteristics of the compressed video, comparing the factors derived from the macroblock size information with the adaptive threshold values, and detecting motion based upon the comparing when at least one of the factors exceeds at least one of the adaptive threshold values. In some embodiments, detecting the motion can include performing spatio-temporal filtering on macroblocks in which the motion is detected or performing spatio-temporal filtering on at least one non-motion macroblock.

Abstract: According to exemplary methods of training a convolutional neural network, input images are received into a computerized device having an image processor. The image processor evaluates the input images using first convolutional layers. The number of first convolutional layers is based on a first size for the input images. Each layer of the first convolutional layers receives layer input signals comprising features of the input images and generates layer output signals that include signals from the input images and ones of the layer output signals from previous layers within the first convolutional layers. Responsive to an input image being a second size larger than the first size, additional convolutional layers are added to the convolutional neural network. The number of additional convolutional layers is based on the second size in relation to the first size. The additional convolutional layers are initialized using weights from the first convolutional layers.

Abstract: An image processing device includes a contrasting correction unit, a color analysis unit, an object detection unit, and an object relation analysis unit. The contrasting correction unit creates a contrasting corrected image by correcting contrasting of an input image captured by a vehicle camera. The color analysis unit creates a color corrected image by correcting colors of the input image. The object detection unit detects a main sign included in the input image based on the contrasting corrected image and detects an auxiliary sign included in the input image based on the color corrected image. The object relation analysis unit recognizes a traffic sign as a combination of a main sign and auxiliary sign by associating the main sign and the auxiliary sign with each other based on a positional relationship between the main and auxiliary signs, which are detected by the object detection unit, in the input image.

Abstract: A method for reducing grid line artifacts in an X-ray image is disclosed, which includes acquiring an X-ray image by scanning an object, wherein the X-ray image comprises grid line artifacts; decomposing the X-ray image into a high frequency image and a low frequency image, wherein the high frequency image comprises the grid line artifacts; filtering the high frequency image to reduce the grid line artifacts in the high frequency image so as to obtain a filtered high frequency image; and combining the filtered high frequency image with the low frequency image to reconstruct an output image. A system adopting the above method is also disclosed.

Abstract: In an example embodiment, a web page is obtained using a web page address stored in a first record and is parsed to extract one or more images from the web page along with a first plurality of features for each of the one or more images from the web page. Information about each image of the web page and the extracted first plurality of features for the web page are input into a supervised machine learning classifier to calculate a logo confidence score for each image of the web page, the logo confidence score indicating the probability that the image is an organization logo. In response to a particular image in the web page having a logo confidence score transgressing a first threshold, the particular image is injected into an organization logo field of the first record.

Abstract: System and method for processing images of concrete are provided. Image data captured from a construction site may be obtained. The image data may be analyzed to identify regions of the image data that depict concrete. The image data may be analyzed to determine quality indications associated with concrete depicted in the image data, for example in a region identified above. In some examples, the quality indications may comprise an indication of the durability of the concrete, of the strength of the concrete, and so forth.

Abstract: Described herein are a system and methods for generating a record of objects, as well as respective positions for those objects, with respect to a user. In some embodiments, a user may use a user device to scan an area that includes one or more objects. The one or more objects may be identified from image information obtained from the user device. Positional information for each of the one or more objects may be determined from depth information obtained from a depth sensor installed upon the user device. In some embodiments, the one or more objects may be mapped to object models stored in an object model database. The image information displayed on the user device may be augmented so that it depicts the object models associated with the one or more objects instead of the actual objects.