Abstract: A system is provided for adaptively conformed imaging of work pieces having disparate configurations, which comprises a mount unit for holding at least one work piece, and an imaging unit for capturing images of the work piece held by the mount unit. At least one manipulator unit is coupled to selectively manipulate at least one of the mount and imaging units for relative displacement therebetween. A controller coupled to automatically actuate the manipulator and imaging units executes scene segmentation about the held work piece, which spatially defines at least one zone of operation in peripherally conformed manner about the work piece. The controller also executes an acquisition path mapping for the work piece, wherein a sequence of spatially offset acquisition points are mapped within the zone of operation, with each acquisition point defining a vantage point for the imaging unit to capture an image of the work piece from.

Abstract: A method and apparatus for (a) receiving a three-dimensional (3D) point cloud from a depth sensor that is oriented towards an open end of a shipping container, the point cloud comprising a plurality of points that each have a respective depth value, (b) segmenting the received 3D point cloud among a plurality of grid elements, (c) calculating a respective loaded-container-portion grid-element volume for each grid element, (d) calculating a loaded-container-portion volume of the shipping container by aggregating the calculated respective loaded-container-portion grid-element volumes, (e) calculating an estimated fullness of the shipping container based on the loaded-container-portion volume and a capacity of the shipping container; and (f) outputting the calculated estimated fullness of the shipping container.

Abstract: A service can perform optical character recognition (OCR) on an image of a record to determine a first set of information items about the record. A second set of information items can be identified that are likely part of the record but not determinable from performing OCR on the image. Another resource can be utilized to determine the second set of information items. A classification for the record can be determined based on first and second sets of information items. The record can be associated with a financial resource of the user based at least in part on the classification.

Abstract: Object identification through image matching can utilize ratio and other data to accurately identify objects having relatively few feature points otherwise useful for identifying objects. An initial image analysis attempts to locate a “scalar” in the image, such as may include a label, text, icon, or other identifier that can help to narrow a classification of the search, as well as to provide a frame of reference for relative measurements obtained from the image. By comparing the ratios of dimensions of the scalar with other dimensions of the object, it is possible to discriminate between objects containing that scalar in a way that is relatively robust to changes in viewpoint. A ratio signature can be generated for an object for use in matching, while in other embodiments a classification can identify priority ratios that can be used to more accurately identify objects in that classification.

Abstract: A display control method executed by a processor included in a terminal device that includes a display and a camera disposed at a display surface side of the display, the display control method includes acquiring a first image taken by the camera, the first image including a second image of a face; calculating a proportion of a region of the second image to a region of the first image; determining whether the proportion is equal to or higher than a threshold; displaying the first image on the display when it is determined that the proportion is equal to or higher than the threshold; and restraining the first image from being displayed on the display when it is determined that the proportion is not equal to or higher than the threshold.

Abstract: Various embodiments described herein notifying users regarding photos in which they may appear and suggest photo tags accordingly. Subject to user preferences and privacy settings, facial recognition with respect to a specific user of a social networking system may be performed on one or more photos added by, or otherwise associated with, other entities of the social networking system. For those photos in which the specific user is facially recognized, a suggested photo tag for the specific user may be associated with the recognized photos and the specific user may be alerted accordingly. Depending on the embodiment, the specific user may be provided with an option to confirm the suggested photo tag, decline the suggested photo tag, or do nothing. In the event the specific user declines the suggested photo tag with respect to a particular photo, other users may be prevented from tagging the specific user with respect to the particular photo.

Abstract: Systems, methods, devices, media, and computer readable instructions are described for local image tagging in a resource constrained environment. One embodiment involves processing image data using a deep convolutional neural network (DCNN) comprising at least a first subgraph and a second subgraph, the first subgraph comprising at least a first layer and a second layer, processing, the image data using at least the first layer of the first subgraph to generate first intermediate output data; processing, by the mobile device, the first intermediate output data using at least the second layer of the first subgraph to generate first subgraph output data, and in response to a determination that each layer reliant on the first intermediate data have completed processing, deleting the first intermediate data from the mobile device. Additional embodiments involve convolving entire pixel resolutions of the image data against kernels in different layers if the DCNN.

Abstract: Provided is an apparatus for measuring a quality of a holographic image. The apparatus includes: a hologram image reconstruction unit configured to perform a hologram image; a superimposed focus image generation unit configured to collect an area that is in focus from reconstructed images and superimpose into a single image; and a hologram image quality measurement unit configured to perform an image quality evaluation for the superimposed focus image.

Abstract: An image recognition (IR) computing device is provided herein, the IR computing device configured to receive a search request from a user computing device instructing the IR computing device to conduct a search for a subject clothing item pictured in a subject image, the search request including the subject image. The IR computing device is further configured to analyze the subject image and compare a plurality of vendor images to the subject image. The IR computing device may employ an object recognition component to analyze and compare the images. The IR computing device is further configured to generate a list of potential matches to the subject image, transmit the list of potential matches to the user computing device for display to a user within a clothing match app, and receive an indication from the user computing device of whether the search was successful or unsuccessful.

Abstract: An image processing apparatus includes a first obtaining unit to obtain a number of images in which a pair of a first person and a second person simultaneously appears, out of a plurality of images. A detection unit detects whether the pair appears in a target image group, which is one of a plurality of image groups into which the plurality of images is classified. In determining whether the pair appears in the target image group, it is determined that the pair appears in the target image group not only in a case when the target image group includes an image in which the first person and the second person simultaneously appear, but also, in a case when the target image group includes images in which the first person and the second person appear separately.

Abstract: Methods and systems for recognizing people in images with increased accuracy are disclosed. In particular, the methods and systems divide images into a plurality of clusters based on common characteristics of the images. The methods and systems also determine an image cluster to which an image with an unknown person instance most corresponds. One or more embodiments determine a probability that the unknown person instance is each known person instance in the image cluster using a trained cluster classifier of the image cluster. Optionally, the methods and systems determine context weights for each combination of an unknown person instance and each known person instance using a conditional random field algorithm based on a plurality of context cues associated with the unknown person instance and the known person instances. The methods and systems calculate a contextual probability based on the cluster-based probabilities and context weights to identify the unknown person instance.

Abstract: Methods and systems for finding patterns in a design for a specimen are provided. One system includes one or more computer subsystems configured for searching for a target pattern in a design for a specimen to thereby find multiple instances of the target pattern in the design. The one or more computer subsystems are also configured for separating the multiple instances of the target pattern into different groups based on information for surrounding patterns within a predefined window around the target pattern such that each of the different groups corresponds to a different combination of the target pattern and the surrounding patterns.

Abstract: A face detection device for detecting the face of a person in an input image includes the a face detection circuit, a signal processing circuit, and a controller. The face detection circuit includes a hardware circuit that is configured to detect a face in an input image. The signal processing circuit is configured to perform signal processing based on an input image signal in accordance with a rewritable program including a face detection program for detecting a face in an input image. The controller is configured to allow the face detection circuit and the signal processing circuit to perform face detection on an image of a frame or on respective images of adjacent frames among consecutive frames, and to control face detection by the signal processing circuit on the basis of a face detection result obtained by the face detection circuit.

Abstract: A method for improving classification results of a classifier including receiving classification results for a plurality of elements that have been classified by a classifier as one of a plurality of classes, constructing a graph having a plurality of nodes, each node corresponding to one of the elements, and a plurality of labels, each label corresponding to one of the classes, adding edges between nodes corresponding to related elements, adding edges between each node and each label, and using a graph cut algorithm to cut edges to a node and partition the graph into classes, the graph cut algorithm using as input the classification results for the element corresponding to that node and related elements.

Abstract: Joint depth estimation and semantic labeling techniques usable for processing of a single image are described. In one or more implementations, global semantic and depth layouts are estimated of a scene of the image through machine learning by the one or more computing devices. Local semantic and depth layouts are also estimated for respective ones of a plurality of segments of the scene of the image through machine learning by the one or more computing devices. The estimated global semantic and depth layouts are merged with the local semantic and depth layouts by the one or more computing devices to semantically label and assign a depth value to individual pixels in the image.

Abstract: A system, article, and method of feature matching for multiple images.

Abstract: A method and apparatus for (a) receiving a three-dimensional (3D) point cloud from a depth sensor that is oriented towards an open end of a shipping container, the point cloud comprising a plurality of points that each have a respective depth value, (b) segmenting the received 3D point cloud among a plurality of grid elements, (c) calculating a respective loaded-container-portion grid-element volume for each grid element, (d) calculating a loaded-container-portion volume of the shipping container by aggregating the calculated respective loaded-container-portion grid-element volumes, (e) calculating an estimated fullness of the shipping container based on the loaded-container-portion volume and a capacity of the shipping container; and (f) outputting the calculated estimated fullness of the shipping container.

Abstract: Systems, methods, and computer media for implementing convolutional neural networks efficiently in hardware are disclosed herein. A memory is configured to store a sparse, frequency domain representation of a convolutional weighting kernel. A time-domain-to-frequency-domain converter is configured to generate a frequency domain representation of an input image. A feature extractor is configured to access the memory and, by a processor, extract features based on the sparse, frequency domain representation of the convolutional weighting kernel and the frequency domain representation of the input image. The feature extractor includes convolutional layers and fully connected layers. A classifier is configured to determine, based on extracted features, whether the input image contains an object of interest. Various types of memory can be used to store different information, allowing information-dense data to be stored in faster (e.g., faster access time) memory and sparse data to be stored in slower memory.

Abstract: In one embodiment, a method for detecting faces in video image frames includes comparing a current image frame to a previously processed image frame to determine similarity, discarding the current image frame if the current image frame and the previously processed image frame are, detecting at least one detected facial image in the current image frame, comparing the at least one detected facial image to at least one most recently stored facial image stored in a most recently used (MRU) cache to determine similarity, discarding the at least one detected facial image if the at least one detected facial image and the at least one most recently stored facial image are similar; and storing the at least one detected facial image in the MRU cache if the at least one detected facial image and the at least one most recently stored facial image are not similar.

Abstract: An image processing apparatus includes: a holding unit that holds a plurality of images; a condition checking unit that checks imaging conditions of the plurality of images; a collation determining unit that determines whether to collate images among the plurality of images based on the imaging conditions of the images; a collation unit that collates the images determined to be collated by the collation determining unit to obtain a degree of similarity; and a classifying unit that classifies the collated images into a same category when the degree of similarity is equal to or greater than a predetermined threshold.