Abstract: According to one embodiment, a reading system includes a processing device. The processing device includes an extractor, a line thinner, a setter, and an identifier. The extractor extracts a partial image from an input image. A character of a segment display is imaged in the partial image. The segment display includes a plurality of segments. The line thinner thins a cluster of pixels representing a character in the partial image. The setter sets, in the partial image, a plurality of determination regions corresponding respectively to the plurality of segments. The identifier detects a number of pixels included in the thinned cluster for each of the plurality of determination regions, and identifies the character based on a detection result.

Abstract: An object recognition method is provided. The method includes: detecting an occlusion region of an object in an image, to obtain a binary image; obtaining occlusion binary image blocks; querying a mapping relationship between occlusion binary image blocks and binary masks included in a binary mask dictionary to obtain binary masks corresponding to the occlusion binary image blocks; synthesizing the binary masks queried based on each of the occlusion binary image blocks, to obtain a binary mask corresponding to the binary image; and determining a matching relationship between the image and a prestored object image, based on the binary mask corresponding to the binary image, a feature of the prestored object image, and a feature of the to-be-recognized image.

Abstract: An image encoding method including: a constraint information generating step of generating tile constraint information indicating whether or not there is a constraint in filtering on boundaries between adjacent tiles among a plurality of tiles obtained by dividing a picture, and storing the tile constraint information into a sequence parameter set; and a filter information generating step of generating, for each of the boundaries, one of a plurality of filter information items respectively indicating whether or not filtering is executed on the boundaries, and storing the plurality of filter information items into a plurality of picture parameter sets, wherein, in the filter information generating step, the plurality of filter information items which indicate identical content are generated when the tile constraint information indicates that there is the constraint in the filtering.

Abstract: In an object recognition apparatus, a storage unit stores a table in that a plurality of feature amounts are associated with each object having feature points of respective feature amounts. An object region detection unit detects object regions of a plurality of objects from an input image. A feature amount extraction unit extracts feature amounts of feature points from the input image. A refining unit refers to the table, and refines from all objects of recognition subjects to object candidates corresponding to the object regions based on feature amounts of feature points belonging to the object regions. A matching unit recognizes the plurality of objects by matching the feature points belonging to each of the object regions with feature points for each of the object candidates, and outputs a recognition result.

Abstract: A method of generating a correction plan for a knee of a patient includes obtaining a ratio of reference bone density to reference ligament tension in a reference population. A bone of the knee of the patient may be imaged. From the image of the bone, a first dataset may be determined including at least one site of ligament attachment and existing dwell points of a medial femoral condyle and lateral femoral condyle of the patient on a tibia of the patient. Desired positions of contact in three dimensions of the femoral condyles of the patient with the tibia of the patient may be obtained by determining a relationship in which a ratio of bone density to ligament tension of the patient is substantially equal to the ratio of reference bone density to reference ligament tension.

Abstract: A guidance processing apparatus (100) includes an information acquisition unit (101) that acquires a plurality of different pieces of guidance information on the basis of states of a plurality of people within one or more images, and a control unit (102) that performs control of a plurality of target devices present in different spaces or time division control of a target device so as to set a plurality of different states corresponding to the plurality of pieces of guidance information.

Abstract: A guidance processing apparatus (100) includes an information acquisition unit (101) that acquires a plurality of different pieces of guidance information on the basis of states of a plurality of people within one or more images, and a control unit (102) that performs control of a plurality of target devices present in different spaces or time division control of a target device so as to set a plurality of different states corresponding to the plurality of pieces of guidance information.

Abstract: A method for extracting text from an input image and generating a document includes: generating an edges mask from the input image; generating an edges image that is derived from the edges mask; identifying, within the edges mask, one or more probable text areas; extracting a first set of text characters by performing a first optical character recognition (OCR) operation on each of one or more probable text portions, of the derived edges image, corresponding to each of the probable text areas; generating a modified image by erasing, from the input image, image characters corresponding to the first set of text characters extracted by the first OCR operation; and generating a document by overlaying the extracted first set of text characters on the modified image.

Abstract: The disclosed invention includes systems and methods for training and employing equivariant models for generating representations (e.g., vector representations) of temporally-varying content, such as but not limited to video content. The trained models are equivariant to temporal transformations applied to the input content (e.g., video content). The trained models are additionally invariant to non-temporal transformations (e.g., spatial and/or color-space transformations) applied to the input content. Such representations are employed in various machine learning tasks, such as but not limited to video retrieval (e.g., video search engine applications), identification of actions depicted in video, and temporally ordering clips of the video.

Abstract: The present disclosure provides a tissue density analysis system. The system includes an acquisition module configured to obtain image data and tissue density distribution data; a display module configured to display the obtained tissue density distribution data in one or more charts; a processing module configured to adjust the tissue density distribution data displayed in the one or more charts; and a storage module configured to store the image data, the tissue density distribution data and an instruction.

Abstract: A color conversion section for an imaging device carries out conversion to imaging data imaged by each medical imaging device for eliminating differences in color property of each imaging device, and generates standard color graphic data. To this standard color graphic data, a color conversion section for highlighting a specific tissue carries out color conversion for highlighting a designated specific biotissue, such as a blood vessel, to generate specific tissue highlighted graphic data. To this specific tissue highlighted graphic data, a color conversion section for a monitor carries out conversion for eliminating differences in color property of each monitor to generate display data. Color monitors display graphics based on this display data.

Abstract: Methods and systems for calibrating radiological data associated with a tissue in a subject are provide. Various embodiments described herein analyze a radiological image of the tissue to calculate a raw value indicative of a biological parameter such as metabolic activity in the tissue, and analyze a microscopy image of the tissue to identify a distribution of cells of interest within the tissue. A calibrated value indicative of a biological parameter (e.g. metabolic activity) of cells of interest within the tissue is then calculated, by correcting the raw value based on the identified distribution of cells of interest within the tissue.

Abstract: Aspects relate to systems and methods for the application of computer vision and sensor fusion to assist in the management and operation of a facility. For large facilities, many of the expenses and staffing requirements incurred such as energy, custodial duties, maintenance and security can scale with size rather than usage, and therefore be subject to gross inefficiencies. These challenges may arise from a lack of timely information available with which to make such optimizations and improvements. The approaches disclosed leverage recent advancements in computer vision technology to extract actionable information from raw sensor data collected through-out the facility. This information may be processed and applied in either an autonomous, semi-autonomous, or user driven approach to control and manage a number of processes occurring regularly within a facility, such as lighting, cleaning, and security.

Abstract: Embodiments provide slide navigation technology that addresses challenges in digital pathology of navigating and viewing high resolution slide images. Example systems comprise a virtual slide stage (VSS) having at least one sensor that detects user movement of a target placed on the VSS, and an input component, coupled to the VSS, which provides quick function movement control of the target via quick functions. The systems also comprise a connector component that connects the VSS to a user device and transmits output from the at least one sensor and input component to the user device. The systems further comprise a computer processor, in communication with the VSS, which processes the output using a computational model to generate data representing movement profiles of the target. The computer processor executes a software component, causing the output, translated based on the movement profiles, to be relayed via a viewing application on the user device.

Abstract: Systems and methods for extracting information from documents are provided. In one example embodiment, a computer-implemented method includes obtaining one or more units of text from an image of a document. The method includes determining one or more annotated values from the one or more units of text and determining a set of candidate labels for each annotated value. The method determines each set of candidate labels by performing a search for the candidate labels based at least in part on a language associated with the document and a location of each annotated value. The method includes determining a canonical label for each annotated value based at least in part on the associated candidate labels, and mapping at least one annotated value to an action that is presented to a user based at least in part on the canonical label associated with the annotated value.

Abstract: In some implementations, an adverse environment detection system may receive an image of a road scene associated with a vehicle. The adverse environment detection system may determine a set of features associated with the image based on providing the image to an initial portion of a model. The adverse environment detection system may determine a first condition associated with the image based on providing the set of features to a first processing layer of the model, a second condition associated with the image based on providing the set of features to a second processing layer of the model, and a third condition associated with the image based on providing the set of features to a third processing layer of the model. The first processing layer, the second processing layer, and the third processing layer may process the set of features in parallel.

Abstract: Methods and systems for grouping of media based on similarities between features of media data are provided. A method of managing a plurality of images may include: identifying a threshold distance for clustering the plurality of images based on a degree of similarity between the plurality of images; extracting a plurality of feature vectors corresponding to the plurality of images; and generating at least one cluster comprising at least two images among the plurality of images, based on cosine distances between feature vectors corresponding to the at least two images being less than the threshold distance.

Abstract: The invention relates to a method for the emergency shutdown of hand-guided tools having a drive, wherein the hand-guided tool is connected mechanically to at least one camera and the camera and/or the tool is/are provided with an evaluation unit having image processing software, in which the following steps are provided: activating the camera, monitoring a predefined danger area of the hand-guided tool by means of the camera, processing and evaluating the captured image data by means of the evaluation unit and the image processing software with regard to the presence of a human body part in the danger area, and generating a warning signal, slowing down the drive of the hand-guided tool and/or stopping the drive of the hand-guided tool if a human body part is present in the danger area.

Abstract: Geometric extraction is performed on an unstructured document by recognizing textual blocks on at least a portion of a page of the unstructured document, generating bounding boxes that surround and correspond to the textual blocks, determining search paths having coordinates of two endpoints and connecting at least two bounding boxes, and generating a graph representation of the at least a portion of the page, the graph representation including the plurality of textual blocks, the coordinates of the vertices of each bounding box and the coordinates of the two endpoints of each search path.

Abstract: System, methods, and other embodiments described herein relate to a manner of training a depth prediction system using bounding boxes. In one embodiment, a method includes segmenting an image to mask areas beyond bounding boxes and identify unmasked areas within the bounding boxes. The method also includes training a depth model using depth losses from comparing weighted points associated with pixels of the image within the unmasked areas to ground-truth depth. The method also includes providing the depth model for object detection.