Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for visual authentication. In some implementations, a method may include obtaining images of a person at a property; detecting a discontinuity in an appearance of the person in the images of the person at the property; determining that the discontinuity does not correspond to a known occlusion; and providing an indication of a potential spoofing attack.

Abstract: An image analysis apparatus includes a person information acquisition unit configured to analyze a captured image of a monitored space imaged by a camera so as to acquire information of a person imaged in the captured image, and a hidden state detection unit configured to detect occurrence of a hidden state in which a plurality of the persons are imaged to overlap in the captured image.

Abstract: A drink ordering and dispensing system. A drink is ordered, and placed into a database. When drinks are poured, they are associated with the drinks that have been in the database. Scale is used to hold all the bottles. Whenever a bottle is removed or replaced on the scale, the total weight of the scale changes, and hence the weight change of the bottle can be determined. Once the drink is poured, the id of the bottle, and the weight on the scale before and after pouring is used to determine if the drink has been over poured. The scale includes a camera that can be used to identify the bottle and the server who does the pouring. The server who does the pouring can be identified using a biometric scan of the person, obtained using the same camera that identifies the bottle being poured.

Abstract: Systems, computer program products, and methods are described herein for image categorization and recognition using unsupervised learning. The present disclosure is configured to receive an unseen image; implement a first low pass filter on the unseen image to generate a first version of the unseen image; implement a second low pass filter on the first version of the unseen image to generate a second version of the unseen image; determine a subset of the second version of the recorded images that matches the second version of the unseen image; retrieve a subset of first version of recorded images associated with the subset of second version of recorded images; and determine a first recorded image from the subset of the first version of the recorded images that matches the first version of the unseen image.

Abstract: Disclosures herein teach applying a set of sections spanning a down-sampled version of an image of a road-scene to a low-fidelity classifier to determine a set of candidate sections for depicting one or more objects in a set of classes. The set of candidate sections of the down-sampled version may be mapped to a set of potential sectors in a high-fidelity version of the image. A high-fidelity classifier may be used to vet the set of potential sectors, determining the presence of one or more objects from the set of classes. The low-fidelity classifier may include a first Convolution Neural Network (CNN) trained on a first training set of down-sampled versions of cropped images of objects in the set of classes. Similarly, the high-fidelity classifier may include a second CNN trained on a second training set of high-fidelity versions of cropped images of objects in the set of classes.

Abstract: Methods and systems for developing a sizing system through categorization and selection of prototypes, which can be regarded as the most appropriate fit model, is described. Once categorized and prototypes are selected, recommendations for the sizing of a target body part may be issued.

Abstract: Methods and devices for encoding a point cloud. More than one frame of reference is identified and a transform defines the relative motion of a second frame of reference to a first frame of reference. The space is segmented into regions and each region is associated with one of the frames of reference. Local motion vectors within a region are expressed relative to the frame of reference associated with that region. Occupancy of the bitstream is entropy encoded based on predictions determined using the location motion vectors and the transform associated with the attached frame of reference.

Abstract: Described here are systems and methods for quantifying vessel features in non-contrast microvasculature images obtained with an ultrasound imaging system. Vessel features that are quantified include, but are not limited to, vessel structure features (e.g., number of vessels, vessel density, number of branch points), vessel diameter, and vessel tortuosity. Morphological filtering is used to generate vessel segments from which the quantitative vessel features can be reliably quantified.

Abstract: The present disclosure provides an object detection method. The method includes: acquiring a scene image of a scene; acquiring a three-dimensional point cloud corresponding to the scene; segmenting the scene image according to the three-dimensional point cloud corresponding to the scene to generate a plurality of region proposals; and performing object detection on the plurality of region proposals to determine a target object to be detected in the scene image. In addition, The present disclosure also provides an object detection device, a terminal device, and a medium.

Abstract: An electronic apparatus and a control method thereof are provided. The control method includes acquiring a plurality of words, acquire a plurality of word combinations by combining the plurality of words, and acquiring first scores indicating the sentence completeness of each of the plurality of word combinations by inputting each of the plurality of word combinations to a first a language model for identifying a sentence completeness, based on all the first scores with respect to each of the plurality of word combinations being identified to be less than a predetermined value, acquire second scores for each of the plurality of word combinations by inputting each of the plurality of word combinations to a sentence separation model for identifying an accuracy of a word combination, identifying one word combination among the plurality of word combinations based on the second scores, and providing the identified one word combination to a translation model which performs translation.

Abstract: Methods, systems, and apparatuses related to autonomous vehicle object detection are described. An autonomous vehicle can capture an image corresponding to an unknown object disposed within a sight line of the autonomous vehicle. Processing resources available to a plurality of memory devices associated with the autonomous vehicle can be reallocated in response to capturing the image and an operation involving the image corresponding to the unknown object to classify the unknown object can be performed using the reallocated processing resources.

Abstract: The present development is a method for providing stable visualization of tubular objects. The method simplifies visualization using a Fly-Ln approach without loss of internal surface details. The method uses graphical programming, and can be easily integrated with commercially available visualization programs, such as Virtual Colonoscopy (VC) or Computed Tomography Colonography (CTC).

Abstract: A method for image processing is disclosed herein. A computer system obtains a first image and a second image acquired by an imaging device. The computer system determines a matrix relating a first set of image points in the first image to a second set of image points in the second image. Based on the matrix, the computer system determines a set of parameters of the imaging device and a rotational relationship between the first image and the second image corresponding to poses of the imaging device. In response to determining that the first image and the second image are aligned based on the set of parameters of the imaging device and the rotational relationship between the first image and the second image, the computer system generates a composite image of the first image and the second image and causes display of the composite image.

Abstract: Embodiments of the present disclosure relate performing registration of a first image to a second image where the first image is undistorted to linear space before applying a geometric transformation matrix to modify the first image to align with the second image. The geometric transformation matrix may be a linear matrix that causes the undistorted version of the first image to make translation movement, rotational movement or both. The undistorted and modified first image is then reverted back to nonlinear distorted space. Then the reverted first image may be warped to better align with the second image for fusing with the second image. In this way, visual distortions in the fused image such as wobbling may be reduced or eliminated.

Abstract: The present disclosure is directed to apparatuses, systems and methods for automatically classifying images of occupants inside a vehicle. More particularly, the present disclosure is directed to apparatuses, systems and methods for automatically classifying images of occupants inside a vehicle by comparing current image feature data to previously classified image features.

Abstract: A magnetic resonance imaging device according to an embodiment includes a processing circuitry. The processing circuitry obtains, from an image of a test subject taken by an optical photographing device, image-related information regarding at least either the test subject or a radio frequency (RF) coil attached to the test subject. Then, the processing circuitry selects statistical information about the attachment position of the RF coil based on the image-related information. Subsequently, the processing circuitry outputs the attachment position of the RF coil corresponding to the statistical information.

Abstract: Product spaces for containers of non-discretized items are defined by sets of points in three-dimensional space. When a customer breaches or contacts a product space established for a container of the non-discretized items, video feeds representing the product space are displayed to an associate in a web page or another user interface. By interacting with the user interface, the associate may view the video feeds and make a determination as to whether the customer received any of the non-discretized items from the container, and to confirm an identity of the customer accordingly.

Abstract: The disclosure includes a system and method for detecting a synthetically generated image including receiving a first image; generating, based on the first image, a first image attribute distribution; and determining, based on the first image attribute distribution, whether the first image is synthetically generated; and issuing, responsive to determining that the first image is synthetically generated, a rejection.

Abstract: In an image comparison method, an original reference image and an original test image are obtained. The original reference image and the original test image are binarized to obtain a reference binary image and a test binary image. The reference binary image and the test binary image are detected edges to obtain a reference edge image and a test edge image. A morphological expansion is performed on the reference edge image to obtain an expanded reference edge image. An OR operation is performed on the extended reference edge image and the test edge image to obtain an extended test edge image. An XOR operation is performed on the expanded reference edge image and the expanded test edge image. The method improves the accuracy of image comparison.

Abstract: The present disclosure is directed to apparatuses, systems and methods for automatically classifying digital images of occupants inside a vehicle. More particularly, the present disclosure is directed to apparatuses, systems and methods for automatically classifying digital images of occupants inside a vehicle by comparing current image data to previously classified image data.