Abstract: The present disclosure relates to a method for 3D reconstruction from satellite imagery using deep learning, said method comprising providing (101) at least two overlapping 2D satellite images, providing (102) imaging device parameters for the at least two overlapping 2D satellite images, providing (103) at least one trained Machine Learning Network, MLN, able to predict depth maps, said trained MLN being trained on a training set comprising multi-view geocoded 3D ground truth data and predicting (104) a depth map of the at provided at least two 2D satellite images using the trained at least one MLN and based on the corresponding imaging device parameters.

Abstract: A computer program product may cause one or more processors to generate stereoscopic images of one or more 3D models within a 3D model space. As part of the generation of the stereoscopic images, special case surfaces that are non-flat and specularly reflective or refractive are rendered in a special manner. The special manner involves rendering a texture for the special case surface based on a third projection corresponding to a third viewpoint that is spaced from both a first viewpoint (i.e., a left eye viewpoint) and a second viewpoint (i.e., a right eye viewpoint). Accordingly, when rendering first and second images (i.e., images corresponding respectively to the first and second viewpoints), the texture corresponding to the third viewpoint may be applied to the special case surface in both the first and second images.

Abstract: The disclosure describes one or more embodiments of systems, methods, and non-transitory computer-readable media that utilize a sharpness map that includes information on how to filter a displacement map on a per-texel basis to preserve sharp features while sampling a displacement map. For instance, the disclosed systems utilize a sharpness map that encodes combinable patterns to represent discontinuities of features within a displacement map. In some embodiments, the disclosed systems generate a sharpness map having texels encoded with discontinuity configurations that are referenced to control filtering (e.g., via interpolation) of a displacement map such that sharp features within the displacement map are not lost (due to smoothing during interpolation).

Abstract: Apparatus and associated methods relate to providing an optical display apparatus that can be used to make a light source display variable apparent sizes in response to light intensities emitted by the light source. In an illustrative example, the optical display apparatus may have a first baffle arranged on the top of a light source. The optical display apparatus may also include a second baffle, the first baffle may be nested in the second baffle such that a first intensity of a first beam of light guided within the first baffle is stronger than a second intensity of the second beam of light guided between the first baffle and the second baffle. By adjusting the light intensities, different display regions of a translucent diffuser may be lit, which may provide controllable apparent sizes of a light structure.

Abstract: Systems and methods for generating three-dimensional models with correlated three-dimensional and two dimensional imagery data are provided. In particular, imagery data can be captured in two dimensions and three dimensions. Imagery data can be transformed into models. Two-dimensional data and three-dimensional data can be correlated within models. Two-dimensional data can be selected for display within a three-dimensional model. Modifications can be made to the three-dimensional model and can be displayed within a three-dimensional model or within two-dimensional data. Models can transition between two dimensional imagery data and three dimensional imagery data.

Abstract: An image processing system includes a computing platform having a hardware processor and a system memory storing an image augmentation software code, a three-dimensional (3D) shapes library, and/or a 3D poses library. The image processing system also includes a two-dimensional (2D) pose estimation module communicatively coupled to the image augmentation software code. The hardware processor executes the image augmentation software code to provide an image to the 2D pose estimation module and to receive a 2D pose data generated by the 2D pose estimation module based on the image. The image augmentation software code identifies a 3D shape and/or a 3D pose corresponding to the image using an optimization algorithm applied to the 2D pose data and one or both of the 3D poses library and the 3D shapes library, and may output the 3D shape and/or 3D pose to render an augmented image on a display.

Abstract: Example implementations may relate to methods and systems for detecting an event in a physical region within a physical space. Accordingly, a computing system may receive from a subscriber device an indication of a virtual region within a virtual representation of the physical space such that the virtual region corresponds to the physical region. The system may also receive from the subscriber a trigger condition associated with the virtual region, where the trigger condition corresponds to a particular physical change in the physical region. The system may also receive sensor data from sensors in the physical space and a portion of the sensor data may be associated with the physical region. Based on the sensor data, the system may detect an event in the physical region that satisfies the trigger condition and may responsively provide to the subscriber a notification that indicates that the trigger condition has been satisfied.

Abstract: Techniques for estimating a perimeter of a room environment at least partially enclosed by a set of adjoining walls using posed images are disclosed. A set of images and a set of poses are obtained. A depth map is generated based on the set of images and the set of poses. A set of wall segmentation maps are generated based on the set of images, each of the set of wall segmentation maps indicating a target region of a corresponding image that contains the set of adjoining walls. A point cloud is generated based on the depth map and the set of wall segmentation maps, the point cloud including a plurality of points that are sampled along portions of the depth map that align with the target region. The perimeter of the environment along the set of adjoining walls is estimated based on the point cloud.

Abstract: Embodiments include systems and methods for determining a 6D pose estimate associated with an image of a physical 3D object captured in a video stream. An initial 6D pose estimate is inferred and then further iteratively refined. The video stream may be frozen to allow the user to tap or touch a display to indicate a location of the user-input keypoints. The resulting 6D pose estimate is used to assist in replacing or superimposing the physical 3D object with digital or virtual content in an augmented reality (AR) frame.

Abstract: According to an aspect, a method includes receiving a first three-dimensional model (3D) model of at least a body part of a person, receiving a second 3D model of a wearable device, and predicting, by at least one machine-learning (ML) model, a plurality of contact points between the first 3D model and the second 3D model.

Abstract: In an image display system that is equipped with a camera that images a figure of a visitor of a theme park in front of a mirror device and a background, a server that processes an image of the visitor imaged by the camera and that generates display data, and a display device that displays the display data generated by the server on the mirror device, the server includes a database that stores image data on a character, and generates the display data after replacing part of the image of the visitor imaged by the camera with part of an image of the character selected by the visitor with reference to the database.

Abstract: A system and method for determining a location for a surgical jig in a surgical procedure includes providing a mixed reality headset, a 3D spatial mapping camera, an infrared or stereotactic camera, and a computer system configured to transfer data to and from the mixed reality headset and the 3D spatial mapping camera. The system and method also include attaching a jig to a bone, mapping the bone and jig using the 3D spatial mapping camera, and then identifying a location for the surgical procedure using the computer system. Then the system and method use the mixed reality headset to provide a visualization of the location for the surgical procedure.

Abstract: Methods and systems for manufacture of a garment are disclosed, in particular for generating fabrication data for manufacture of a garment, where said garment is for regulation of a body region of a wearer of the garment. Measurement data for the body region of the wearer is obtained, and the measurement data is modified to simulate a regulating effect for the garment. The modified measurement data is used to generate the fabrication data for manufacturing the garment. The measurement data may be obtained for an unregulated state of the body region of the wearer, the measurement data may be modified to simulate a regulated state of the body region of the wearer. An initial form of the garment may be manufactured using the fabrication data, and the measurement data used to obtain a three-dimensional model of the body region. The initial form of the garment may then be compared to the three-dimensional model; and the comparison used to modify the initial form of the garment.

Abstract: An apparatus includes an extract unit configured to extract features of a first image based on an electromagnetic wave in a first frequency band, an acquire unit configured to acquire motion information about the features, a classify unit configured to classify the features into a first group and a second group based on the motion information, and a remove unit configured to remove, from the first image, a signal corresponding to the feature belonging to the first group.

Abstract: A method for authenticating an object, comprising determining a physical dispersion pattern of a set of elements, determining a physical characteristic of the set of elements which is distinct from a physical characteristic producible by a transfer printing technology, determining a digital code associated with the object defining the physical dispersion pattern, and authenticating the object by verifying a correspondence of the digital code with the physical dispersion pattern, and verifying the physical characteristic.

Abstract: Provided are a method for processing multimodal images, an apparatus, a device and a storage medium. Multiple types of vision sensors are disposed in first preset identity recognition scenario.

Abstract: Methods for image-based detection of the tops of sample tubes used in an automated diagnostic analysis system may be based on a convolutional neural network to pre-process images of the sample tube tops to intensify the tube top circle edges while suppressing the edge response from other objects that may appear in the image. Edge maps generated by the methods may be used for various image-based sample tube analyses, categorizations, and/or characterizations of the sample tubes to control a robot in relationship to the sample tubes. Image processing and control apparatus configured to carry out the methods are also described, as are other aspects.

Abstract: Systems and methods are provided for image classification using histograms of oriented gradients (HoG) in conjunction with a trainer. The efficiency of the process is greatly increased by first establishing a bitmap which identifies a subset of the pixels in the HoG window as including relevant foreground information, and limiting the HoG calculation and comparison process to only the pixels included in the bitmap.

Abstract: The present disclosure discloses a nonlinear all-optical deep-learning system and method with multistage space-frequency domain modulation. The system includes an optical input module, configured to convert input information to optical information, a multistage space-frequency domain modulation module, configured to perform multistage space-frequency domain modulation on the optical information generated by the optical input module so as to generate modulated optical information, and an information acquisition module, configured to transform the modulated optical information onto a Fourier plane or an image plane, and to acquire the transformed optical information so as to generate processed optical information.

Abstract: Provided are a method and a system for analyzing image data obtained by photographing a bridge by a drone using artificial intelligence, rapidly and accurately finding a part that requires maintenance of the bridge, and calculating a maintenance solution and a maintenance estimate for the part. The system for maintaining a bridge by analyzing bridge image data received from a drone using artificial intelligence, includes: the drone that photographs the bridge to generate the bridge image data; and an artificial intelligence bridge maintenance apparatus that finds a part of the bridge requiring maintenance, and calculates an optimal maintenance solution and an optimal maintenance estimate necessary for the bridge maintenance.

Abstract: A camera system for defining an inspection space including one or more cameras placed in proximity to a sink or wash station. The camera system is configured such that points within the defined inspection space are visible and may be recorded, but objects outside the defined inspection space are blurred or invisible. This is accomplished by selecting depth of field or by attaching a computing device that is programmed to not record or save information from parts of the image.

Abstract: A system and method for a guided inspection of an apartment, home or other physical space is disclosed. The system and method use augmented reality to guide a user through a physical space. The system and method further use machine learning to automatically detect and classify damage to various physical structures in the physical space. In response to detected damage, the system may prompt a user to move closer to the detected damage for further inspection. The system can also detect obscured structures and prompt a user to make changes to the environment to increase the visibility of the obscured structures.

Abstract: Systems and methods of augmenting objects associated with personal data. A system includes a communication module, a processor, and a memory. The memory stores instructions that, when executed, configure the processor to authenticate a client device based on a credential associated with an account record. The processor receives, from the client device, an indication of a document marker and obtains, from the account record, personal data associated with the document marker. The processor transmits, to the client device, display data based on the personal data. The display data configures the client device to display an augmented reality output based on the personal data and at least one further image of the document. The personal data may include dynamic data varying over time. The display data configuring the client device to display the augmented output may be based on current personal data obtained from the account record.

Abstract: Methods, apparatus, systems, and computer-readable media are set forth for generating and/or utilizing image shortcuts that cause one or more corresponding computer actions to be performed in response to determining that one or more features are present in image(s) from a camera of a computing device of a user (e.g., present in a real-time image feed from the camera). An image shortcut can be generated in response to user interface input, such as a spoken command. For example, the user interface input can direct the automated assistant to perform one or more actions in response to object(s) having certain feature(s) being present in a field of view of the camera. Subsequently, when the user directs their camera at object(s) having such feature(s), the assistant application can cause the action(s) to be automatically performed. For example, the assistant application can cause data to be presented and/or can control a remote device in accordance with the image shortcut.

Abstract: Controlling content in a video media stream is presented. The controlling comprises: imaging a scene with a camera (42) of an electronic device (10); detecting, using a face detection function (22, 113), one or more faces present in the imaged scene; identifying, using an identity recognition function (23, 114), an individual having a face from among the one or more detected faces by determining that the face is a face of an individual having a social relationship on social media with a user of the electronic device (10); seeking approval, using an approval function (24, 115), from the identified individual to participate in the video media stream; and upon an approval from the identified individual to participate in the video media stream, generating the video media stream, using the camera (42) of the electronic device (10), with the face of the identified individual being visible.

Abstract: Aspects of the present disclosure describe systems, methods, and structures that provide action recognition with high-order interaction with spatio-temporal object tracking. Image and object features are organized into into tracks, which advantageously facilitates many possible learnable embeddings and intra/inter-track interaction(s). Operationally, our systems, method, and structures according to the present disclosure employ an efficient high-order interaction model to learn embeddings and intra/inter object track interaction across the space and time for AR. Each frame is detected by an object detector to locate visual objects. Those objects are linked through time to form object tracks. The object tracks are then organized and combined with the embeddings as the input to our model. The model is trained to generate representative embeddings and discriminative video features through high-order interaction which is formulated as an efficient matrix operation without iterative processing delay.

Abstract: Systems, methods, and storage media for processing digital video are disclosed. Exemplary implementations may: receive digital video data at one or more digital video inputs; identify each of the plurality of video frames as one of a keyframe and an intermediate frame; use one or more first sets of software instructions to send at least one of the keyframes and the intermediate frames to one or more processing scripts; use the one or more processing scripts to implement an asynchronous batch processing system on at least one of the keyframes and the intermediate frames by applying one or more second sets of software instructions; and receive an output from the one or more second sets of software instructions.

Abstract: A method and apparatus for detecting a temporal action of a video, an electronic device and a storage medium are disclosed, which relates to the field of video processing technologies. An implementation includes: acquiring an initial temporal feature sequence of a video to be detected; acquiring, by a pre-trained video-temporal-action detecting module, implicit features and explicit features of a plurality of configured temporal anchor boxes based on the initial temporal feature sequence; and acquiring, by the video-temporal-action detecting module, the starting position and the ending position of a video clip containing a specified action, the category of the specified action and the probability that the specified action belongs to the category from the plural temporal anchor boxes according to the explicit features and the implicit features of the plural temporal anchor boxes.

Abstract: A system can obtain a labelled data set, including historic video data and labelled events. The system can divide the labelled data set into historic training/testing data sets. The system can determine, using the historic training data set, a plurality of different parameter configurations to be used by a video encoder to encode a video that includes a plurality of video frames. Each parameter configuration can include a group of pictures (“GOP”) size and a scenecut threshold. The system can calculate an accuracy of event detection (“ACC”) and a filtering rate (“FR”) for each parameter configuration. The system can calculate, for each parameter configuration of the plurality of different parameter configurations, a harmonic mean between the ACC and the FR. The system can then select a best parameter configuration of the plurality of different parameter configurations based upon the parameter configuration that has the highest harmonic mean.

Abstract: A visible light sensor may be configured to sense environmental characteristics of a space using an image of the space. The visible light sensor may be controlled in one or more modes, including a daylight glare sensor mode, a daylighting sensor mode, a color sensor mode, and/or an occupancy/vacancy sensor mode. In the daylight glare sensor mode, the visible light sensor may be configured to decrease or eliminate glare within a space. In the daylighting sensor mode and the color sensor mode, the visible light sensor may be configured to provide a preferred amount of light and color temperature, respectively, within the space. In the occupancy/vacancy sensor mode, the visible light sensor may be configured to detect an occupancy/vacancy condition within the space and adjust one or more control devices according to the occupation or vacancy of the space. The visible light sensor may be configured to protect the privacy of users within the space via software, a removable module, and/or a special sensor.

Abstract: Techniques for automatically detecting objects left behind. An example method includes receiving video frames of a scene from a three-dimensional (3D) camera and establishing, based on 3D depths associated with the video frames, a background of the scene. The method also includes detecting, in the frames, a foreground blob in the scene based on the foreground blob having a 3D depth that is different from the background. The method further includes detecting that the foreground blob has separated into a blob corresponding to a person and a second blob corresponding to an object, based on the person having a 3D depth that is different from the object. The method additionally includes determining that the person has been separated from the object for a threshold, and responsive to determining that the person has been separated from the object for the threshold, generating an alert indicating that the object is left behind.

Abstract: A first imager has a relatively high resolution and a relatively narrow first field-of-view. Information about objects in an environment is detected or captured, and used to steer the first field-of-view of the first imager. The sensor(s) may take the form of a second imager with a relatively lower resolution and relatively wider second field-of-view. Alternatively, other types of sensors, for instance presence/absence sensors may be employed. The first field-of-view may be directed toward an object that satisfies one or more conditions, for instance matching a particular SKU. The first field-of-view may track a moving object, for instance via a tracking mirror and actuator. This approach may be employed in retail locations, for example in grocery or convenience stores, for instance to reduce various forms of theft or in industrial environments.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-readable media, for obtaining a first image from a first sensor; detecting a first object within the first image; extracting discriminative features of the first object into a first feature vector; obtaining a second image from a second sensor; detecting a second object within the second image; extracting discriminative features of the second object into a second feature vector; and determining, based on a comparison between the first feature vector and the second feature vector, that the second object is same as the first object.

Abstract: Systems and methods for night vision combining sensor image types. Some implementations may include obtaining a long wave infrared image from a long wave infrared sensor; detecting an object in the long wave infrared image; identifying a region of interest associated with the object; adjusting a control parameter of a near infrared sensor based on data associated with the region of interest; obtaining a near infrared image captured using the adjusted control parameter of the near infrared sensor; and determining a classification of the object based on data of the near infrared image associated with the region of interest.

Abstract: A method is disclosed for detecting a hazardous situation in road traffic, wherein visible surroundings of a motor vehicle are scanned by way of at least one surroundings monitoring sensor for the presence of a trigger. Upon detection of the trigger, data regarding the surroundings of the motor vehicle is collected by the at least one surroundings monitoring sensor in a trigger-specific radius around the trigger. Pieces of information based on the collected data are transmitted via a communication device to at least one receiver that is independent of the motor vehicle.

Abstract: An information processing apparatus recognizes a target within an actual image by executing processing of a neural network. The information processing apparatus obtains intermediate outputs which correspond to the actual image and a computer graphics (CG) image and which are from a hidden layer when each of the actual image and the CG image has been separately input to the neural network, and causes the neural network to perform learning with use of an evaluation values based on a first evaluation function and a second evaluation function, the first evaluation function causing the evaluation value to decrease as a difference between a recognition result and training data decreases, the second evaluation function causing the evaluation value to decrease as a difference between the intermediate outputs corresponding to the actual image and the CG image decreases.

Abstract: A vehicle control device includes: a recognizer configured to recognize a surrounding situation of a vehicle; and a driving controller configured to control a speed and steering of the vehicle according to a recognition result of the recognizer. The driving controller is configured to stop following travel of following a front vehicle recognized by the recognizer according to a state of a target recognized by the recognizer in a traveling region through which the front vehicle has passed when the following travel is performed. The target is a regulation sign for regulating a part of a lane in which a vehicle is traveling, a regulation sign for regulating a lane, or a guiding sign for guiding a visual line of an occupant of the vehicle.

Abstract: Certain aspects of the present disclosure provide a method for lane marker detection, including: receiving an input image; providing the input image to a lane marker detection model; processing the input image with a shared lane marker portion of the lane marker detection model; processing output of the shared lane marker portion of the lane marker detection model with a plurality of lane marker-specific representation layers of the lane marker detection model to generate a plurality of lane marker representations; and outputting a plurality of lane markers based on the plurality of lane marker representations.

Abstract: The present invention relates to a lighting system 200 of an automotive vehicle comprising: —an image capture device (205) configured to acquire an image (I) of a road (R) of travel of the vehicle, said road (R) comprising lanes marked on the road (110); —a lighting module (215) configured to project road markings on the road (120); wherein said lighting system (200) is configured to filter the projected road markings (120) on the road compared to the lanes marked (110) on the road.

Abstract: Systems and methods for using image analysis techniques to assess unsafe driving conditions by a vehicle operator are discloses. According to aspects, a computing device may access and analyze image data depicting the vehicle operator. In analyzing the image, the computing device may measure certain visible metrics as depicted in the image data and compare the metrics to corresponding threshold values, and may accordingly determine whether the vehicle operator is exhibiting an unsafe driving condition. The computing device may generate and present alerts that indicate any determined unsafe driving condition.

Abstract: A method includes obtaining multiple images of a driver of a vehicle using an imaging sensor associated with the vehicle, where the images of the driver capture the driver's head. The method also includes identifying, in each of at least some of the images, an orientation of the driver's head in the image. The method further includes identifying an average orientation of the driver's head based on at least some of the identified orientations of the driver's head. In addition, the method includes determining whether the driver is inattentive based on the average orientation of the driver's head. Identifying, in each of at least some of the images, the orientation of the driver's head in the image may include identifying a pitch angle and a yaw angle of the driver's head in the image.

Abstract: A method of price text detection by an imaging controller comprises obtaining, by the imaging controller, an image of a shelf supporting labels bearing price text, generating, by the imaging controller, a plurality of text regions containing candidate text elements from the image, assigning, by the imaging controller, a classification to each of the text regions, selected from a price text classification and a non-price text classification. The imaging controller, within each of a subset of the text regions having the price text classification: detects a price text sub-region and generates a price text string by applying character recognition to the price text sub-region. The method further includes presenting, by the imaging controller, the locations of the subset of text regions, in association with the corresponding price text strings.

Abstract: A method, system, and computer program product for automated collection of training data and training object detection models is provided. The method generates a set of reference images for a first set of products. Based on the set of reference images, the method identifies a subset of products within an image stream. Based on the subset of products, a second set of products is determined within the image stream. The method identifies a set of product gaps based on the subset of products and the second set of products. The method generates a product detection model based on the set of reference images, the subset of products, the second set of products, and the product gaps.

Abstract: A reference data extraction unit extracts, from a photographic image from an imaging device that captures an image of an object to be recognized, an image of a reference image region serving as a reference and containing a detection subject in the object. A expanded data extraction unit extracts from the photographic image an image of an expanded-image region, which is an image region that includes the reference image region and is larger than the reference image region. A reduced data extraction unit extracts from the photographic image an image of a reduced-image region, which is an image region that includes the detection subject and is smaller than the reference image region, with the result that a portion of the object is outside of the region. A learning unit uses the extracted images of the image region to learn a dictionary.

Abstract: Convolutional neural networks for detecting objects of interest within images of biological specimens are disclosed. Also disclosed are systems and methods of training and using such networks, one method including: obtaining a sample image and at least one of a set of positive points and a set of negative points, wherein each positive point identifies a location of one object of interest within the sample image, and each negative point identifies a location of one object of no-interest within the sample image; obtaining one or more predefined characteristics of objects of interest and/or objects of no-interest, and based on the predefined characteristics, generating a boundary map comprising a positive area around each positive point the set of positive points, and/or a negative area around each negative point in the set of negative points; and training the convolutional neural network using the sample image and the boundary map.

Abstract: In some implementations, a device may receive an image that depicts handwritten text. The device may determine that a section of the image includes the handwritten text. The device may analyze, using a first image processing technique, the section to identify subsections of the section that include individual words of the handwritten text. The device may reconfigure, using a second image processing technique, the subsections to create preprocessed word images associated with the individual words. The device may analyze, using a word recognition model, the preprocessed word images to generate digitized words that are associated with the preprocessed word images. The device may verify, based on a reference data structure, that the digitized words correspond to recognized words of the word recognition model. The device may generate, based on verifying the digitized words, digital text according to a sequence of the digitized words in the section.

Abstract: Procedural optimization is facilitated by receiving user input for creating or modifying a body of text comprising a procedure, detecting one or more procedural steps associated with the procedure using a procedural step detection module, automatically searching within a corpus of references for one or more related procedural steps using a related procedural step extraction module, automatically identifying one or more outcomes within the corpus of references associated with the one or more related procedural steps using an outcome extraction module, automatically determining whether the one or more outcomes comprise detrimental results using an outcome analysis module, and, in response to determining a set of detrimental outcomes from the one or more outcomes that comprise detrimental results, presenting a detriment indicator within the user interface in association with the one or more procedural steps.

Abstract: An image processing apparatus includes a character recognition processing unit configured to execute character recognition processing on the image data, an acquisition unit configured to acquire one or more character string blocks included in the image data, from the image data, a selection unit configured to select a character string block to be used for setting of a file name, from among the one or more character string blocks acquired by the acquisition unit, and a setting unit configured to set the file name of image data by using a character recognition result of the character recognition processing unit for the character string block selected by the selection unit.

Abstract: Techniques for document segmentation. In an example, a document processing application segments an electronic document image into strips. A first strip overlaps a second strip. The application generates a first mask indicating one or more elements and element types in the first strip by applying a predictive model network to image content in the first strip and a prior mask generated from image content of the first strip. The application generates a second mask indicating one or more elements and element types in the second strip by applying the predictive model network to image content in the second strip and the first mask. The application computes, from a combined mask derived from the first mask and the second mask, an output electronic document that identifies elements in the electronic document and the respective element types.

Abstract: A system, apparatus, method, and computer program product that enhances the efficiency and quality of matches between intellectual content generated by authors and published by peer-reviewed journals. Stable matches between works and stakeholders are modelled, in a nonbinding manner, via a stable-matching problem (Gale-Shapley) algorithm. Via bulletin-board systems acting upon deidentified data, the LONGITUDE function enables journal editors to proactively and reliably commit time and other resources to manuscripts that are most mature and otherwise meritorious. Via the SCRIMSHAW function, COMPASS assists authors in drafting and editing papers that are based on quality-control and journal author guidelines and hence more likely to be accepted by journals. Functions of COMPASS are divisible into two major domains: “matching” and “dispatching.” The “matching” is fulfilled by three subfunctions: LONGITUDE, DECK WEDDING, and FATHOM.