Abstract: Disclosed herein is a method and a system for processing input data for display in an optimal visualization format. The method includes receiving of the input data and identifying one or more visualization formats for displaying the input data based on preferences of the user. An optimal visualization format is identified by applying business rules on each of the identified visualization formats for displaying the input data in the optimal visualization format. In an embodiment, the instant disclosure helps in selecting a most relevant visualization format for displaying the input data. Also, one or more business interpretations and statistics related to the input data are displayed along with the input data, thereby helping users in analyzing and interpreting the input data.

Abstract: The present application discloses a facial image processing apparatus. The facial image processing apparatus includes a memory; and one or more processor. The memory and the at least one processor are communicatively connected with each other. The memory stores computer-executable instructions for controlling the one or more processors to automatically identify a facial feature from a facial image; automatically extract an image portion defining the facial feature from the facial image; perform a detail enhancement process on the image portion to obtain a detail-enhanced image portion corresponding to the image portion; and perform an image composition process to compose the detail-enhanced image portion and the facial image to obtain an enhanced facial image.

Abstract: A control apparatus for generating a control signal for controlling a printer on the basis of an input signal includes: a quantizer configured to generate the control signal by quantizing an intermediate signal generated by multiplication, performed by a first multiplier, of the input signal by a correction gain for controlling a correction amount for a print density error, together with subtraction, performed by a first calculator, from the input signal, of an error diffusion output signal output from a diffusion matrix that determines a distribution of the print density error; a second multiplier configured to multiply the control signal by an adjustment gain determined on the basis of the correction gain; and a second calculator configured to generate an error diffusion input signal to be input to the diffusion matrix on the basis of a signal output from the second multiplier.

Abstract: The present invention concerns a method for assigning a pixel to one of a foreground pixel set and a background pixel set. In this method, if a first condition is met the pixel is assigned to the background pixel set, and if the first condition is not met and a second condition is met, the pixel is assigned to the foreground pixel set. The method comprises a step (S100) of calculating a probability that the pixel belongs to a foreground-relevant object according to a semantic segmentation algorithm, the first condition is that this probability that the pixel belongs to a foreground-relevant object does not exceed a first predetermined threshold, and the second condition is that a difference between this probability that the pixel belongs to a foreground-relevant object and a baseline probability for the pixel equals or exceeds a second predetermined threshold.

Abstract: One variation of a method for tracking stock level within a store includes: dispatching a robotic system to image shelving structures within the store during a scan cycle; receiving images from the robotic system, each image recorded by the robotic system during the scan cycle and corresponding to one waypoint within the store; identifying, in the images, empty slots within the shelving structures; identifying a product assigned to each empty slot based on product location assignments defined in a planogram of the store; for a first product of a first product value and assigned to a first empty slot, generating a first prompt to restock the first empty slot with a unit of the first product during the scan cycle; and, upon completion of the scan cycle, generating a global restocking list specifying restocking of a set of empty slots associated with product values less than the first product value.

Abstract: A key frame detector and method having input interface accepting multiple frames including a previous frame and a current frame, a programmable logic chip coupled to the input interface that receives a background frame, determines a similarity based on a comparison of the current frame with the background frame and discards the current frame if the similarity is greater than a predetermined similarity threshold, determines an absolute difference on a pixel by pixel basis between the current frame and the previous frame and discards the current frame if the absolute difference is less than a predetermined absolute difference threshold, determines a wholeness of an object in the current frame and discards the current frame if the object is not whole, determines whether the current frame with the whole object has been previously provisionally selected and discards if it has and analyzes the Whole object via an object detector.

Abstract: There are disclosed methods and apparatus for manufacture of image inventories from frames of a digital work including audio which corresponds to objects in still images of the digital video work. Objects are detected in each frame's image, and the objects are recognized. Metadata is assigned to the objects, the object metadata linking audio from the digital video work to the corresponding object in the frame's image which produces the audio. For each frame, at least one cryptographic hash of the object metadata is generated, and the hash is written to a node of a transaction processing network.

Abstract: Described is a system for recognition of unseen and untrained patterns. A graph is generated based on visual features from input data, the input data including labeled instances and unseen instances. Semantic representations of the input data are assigned as graph signals based on the visual features. The semantic representations are aligned with visual representations of the input data using a regularization method applied directly in a spectral graph wavelets (SGW) domain. The semantic representations are then used to generate labels for the unseen instances. The unseen instances may represent unknown conditions for an autonomous vehicle.

Abstract: A system and method for recommending clothing or apparel to a user. Activity of a user is detected in order to identify a set of items that are of interest to the user. One or more recommendation parameters may be determined for the used based at least in part on the individual items of clothing/apparel that are of interest to the user. Clothing/apparel content is selected for display to the user based on the recommendation parameters.

Abstract: A facial image that a user desires to look for from among a plurality of detected facial image displayed in a first facial image display area is clicked, and the clicked facial image is displayed in a third facial image display area. A facial image that is similar to the facial image displayed in the third facial image display area and is suitable for printing is looked for among from the plurality of detected facial image displayed in the first facial image display area, and displayed in a second facial image display area. The user clicks the facial image of the person which the user desires to look for from among the facial images displayed in the second facial image display area. The clicked facial image is displayed in the third facial image display area.

Abstract: Aspects of the present invention are directed to system and methods for optimizing identification of locations within a search area using hash values. A hash value represents location information in a single dimension format. Computing points around some location includes calculating an identification boundary that surrounds the location of interest based on the location's hash value. The identification boundary is expanded until it exceeds a search area defined by the location and a distance. Points around the location can be identified based on having associated hash values that fall within the identification boundary. Hashing operations let a system reduce the geometric work (i.e. searching inside boundaries) and processing required, by computing straightforward operations on hash quantities (e.g. searching a linear range of geohashes), instead of, for example, point to point comparisons.

Abstract: A method includes receiving, with a computing system, a video item. The method further includes identifying a first set of features within a first frame of the video item. The method further includes identifying, with the computing system, a second set of features within a second frame of the video item, the second frame being subsequent to the first frame. The method further includes determining, with the computing system, differences between the first set of features and the second set of features. The method further includes assigning a clip category to a clip extending between the first frame and the second frame based on the differences.

Abstract: In embodiments of event image curation, a computing device includes memory that stores a collection of digital images associated with a type of event, such as a digital photo album of digital photos associated with the event, or a video of image frames and the video is associated with the event. A curation application implements a convolutional neural network, which receives the digital images and a designation of the type of event. The convolutional neural network can then determine an importance rating of each digital image within the collection of the digital images based on the type of the event. The importance rating of a digital image is representative of an importance of the digital image to a person in context of the type of the event. The convolutional neural network generates an output of representative digital images from the collection based on the importance rating of each digital image.

Abstract: A method for recognizing a picture, a method and an apparatus for labelling a picture, and a storage medium. The method for recognizing a picture comprises: acquiring a clothes picture labelled with a positioning key point and a clothes wearing region (S310); extracting, based on the locations of the clothes wearing region and the positioning key point, at least one picture region representing a feature region from the clothes picture (S320); and respectively acquiring feature information representing the feature region based on a region feature recognition model corresponding to the feature region (S330). By labelling the positioning key point, a picture representing a clothes content in the clothes picture is positioned, so that the interference of a background content in the clothes picture is reduced.

Abstract: An image collation system comprising: a detection unit that detects an object from an image acquired by imaging a predetermined position using an imaging unit; a tracking unit that tracks an object image of the same object; a selection unit that calculates an evaluated value for each of the object images of the same object and selects the object image of which the evaluated value is equal to or greater than a predetermined value as a best shot image; a collation unit that performs a collation process of collating the best shot image with a registered image and determining whether the object present at the predetermined position is a previously registered object; and a display that displays a performance result of the collation process, the image collation system including a storage unit that stores the best shot image; and a preparation unit that updates or re-prepares an evaluation expression that calculates the evaluated value.

Abstract: Techniques for generating maps without shadows are discussed herein. A plurality of images can be captured by a vehicle traversing an environment representing various perspectives and/or lighting conditions in the environment. A shadow within an image can be identified by a machine learning algorithm trained to detect shadows in images and/or by projecting the image onto a three-dimensional (3D) map of the environment and identifying candidate shadow regions based on the geometry of the 3D map and the location of the light source. Shadows can be removed or minimized by utilizing blending or duplicating techniques. Color information and reflectance information can be added to the 3D map to generate a textured 3D map. A textured 3D map without shadows can be used to simulate the environment under different lighting conditions.

Abstract: Method and system for enhancing visual perception of augmented reality presentation. Location and line-of-sight (LOS) of user wearing see-through head-mounted display (HMD) is detected. A background environment viewed through HMD is determined based on detected location and LOS. Color-attribute(s) of background environment at background location corresponding to user LOS is determined and compared with color-attribute(s) of foreground supplementary image to be displayed on HMD overlaid onto background environment at background location. When an incompatibility condition is detected, visual parameter(s) of supplementary image is adjusted to minimize incompatibility. Color-attribute determination may use information obtained from users previously at background environment, and may be based on user perception resulting from interactions of: geographic location, time when background environment viewed, and user LOS.

Abstract: A computer-implemented method to identify an object in a video is disclosed. The method may include obtaining a video and receiving an indication of one or more foreground regions in the video from a user module based on a user selection within the user module. The method may also include receiving an indication of one or more regions of interest in the foreground regions from the user module based on a user selection within the user module. The method may include determining a human potential size in a plurality of locations in the one or more regions of interest. The method may include generating a background model based on a plurality of frames of the video. The method may also include tracking an object in the one or more regions of interest based on the background model. The method may include identifying the object as a predicted human based on the human potential size.

Abstract: Apparatuses and methods for image processing are provided. The image processing apparatus performs area classification and object detection in an image, and includes a feature map generator configured to generate the feature map of the input image using the neural network, and an image processor configured to classify the areas and to detect the objects in the image using the generated feature map.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in content searching, generating, hosting and/or providing systems supported by or configured with personal computing devices, servers and/or platforms. The systems interact to identify and retrieve data within or across platforms, which can be used to improve the quality of data used in processing interactions between or among processors in such systems. The disclosed systems and methods provide a unified digital content discovery framework that implements a combination of a logistic loss function and a pair-wise loss function for information retrieval. The logistic loss function reduces non-relevant images from appearing in the retrieved results, while the pair-wise loss function ensures that the highest-quality content is included in such results.

Abstract: An audio system has a housing in which are integrated a number of microphones. A programmed processor accesses the microphone signals and produces a number of acoustic pick up beams based groups of microphones, an estimation of voice activity and an estimation of noise characteristics on each beam. Two or more beams including a voice beam that is used to pick up a desired voice and a noise beam that is used to provide information to estimate ambient noise are adaptively selected from among the plurality of beams, based on thresholds for voice separation and thresholds for noise-matching. Other embodiments are also described and claimed.

Abstract: A cardzi display system has software and related hardware that collects images of cards owned by a user by gift or purchase, organizes and shares them. The system has a load screen, a bottom menu, a tutorial function, a log-in and registration screen, a feed, a library, a capture function, an invitation function, and a viewer. The bottom menu leads to the tutorial, the capture function, the library, the feed, and user profile. The log-in screen has a user register initially and later to enter the invention. The feed provides sharing, organizing, and searching of images, and comment capability. The library stores card images captured by a user's camera and then later displayed on the viewer. Upon seeing a cardzi, a user may have others to view it through the invitation function. The system may include a printer configured to print cardzis remotely.

Abstract: A system, method, and computer-readable medium for performing in-database operations, comprising: presenting an automation interface to a user, the user interface automation interface enabling a user to select one or more key performance indicators; instantiating an in-database processing operation, the in-database processing operation performing feature selection from a high dimensional parameter space; executing at least one database statement within the storage system to derive a subset of diagnostic parameters from the high dimensional parameter space.

Abstract: A method and an apparatus are described to classify data. The method and apparatus includes selecting a hypothesis class among entire classes. The method and corresponding apparatus generate output data with regard to the entire classes by applying a classification algorithm to input data, and modify the input data to increase a value of the hypothesis class among the output data in response to a re-classification condition being met. The modified input data is set to be new input data.

Abstract: A method, a device, and a computer program product for identifying objects in image data. The device is enabled to, in response to determining that an object type of a first set of object types is represented in the image data, indicate that the object type is represented in captured image data. The device is further enabled to, in response to determining that no object type of the first set of object types is represented in the image data, determine whether the image data comprises an object characteristic of a specific one of a second set of object types. The device is further enabled to, in response to determining that the image data comprises an object characteristic of the specific one of the second set of object types, indicate that the image data comprises an object characteristic of the specific one of the second set of object types.

Abstract: Target audience content interaction techniques are described. In one or more implementations, a plurality of content is quantified by one or more computing devices as a content feature representation for each of the plurality of content. A plurality of content feature clusters are generated by the one or more computing devices based at least in part on similarity of the content feature representations, one to another. Content cluster interaction data is also created by the one or more computing devices that describes interaction of each of a plurality of users with the plurality of content. A plurality of user interaction clusters are calculated from the content cluster interaction data by the one or more computing devices based at least in part on similarity of the content cluster interaction data of the plurality of users, one to another. The calculated plurality of user interaction clusters are employed by the one or more computing devices to determine content preferences of a target audience.

Abstract: Systems and techniques are disclosed for labeling objects within an image. The objects may be labeled by selecting an option from a plurality of options such that each option is a potential label for the object. An option may have an option score associated with. Additionally, a relation score may be calculated for a first option and a second option corresponding to a second object in an image. The relation score may be based on a frequency, probability, or observance corresponding to the co-occurrence of text associated with the first option and the second option in a text corpus such as the World Wide Web. An option may be selected as a label for an object based on a global score calculated based at least on an option score and relation score associated with the option.

Abstract: Systems and methods are provided for identifying and recommending electronic content to consumers. In accordance with an implementation, one or more elements of electronic content are identified based on video graph data. In an exemplary method, information associated with a first element of video content is received, and corresponding video graph data is obtained. One or more second elements of video content that are similar to the first element of video content are identified based on the obtained video graph data. A subset the first and second elements of video content is subsequently identified for delivery to the user.

Abstract: Systems and techniques are provided for tracking inventory items in an area of real space including inventory display structures. A plurality of cameras are disposed above the inventory display structures. The cameras in the plurality of cameras produce respective sequences of images in corresponding fields of view in the real space. A memory stores a map of the area of real space identifying inventory locations on inventory display structures. The system is coupled to a plurality of cameras and uses the sequences of images produced by at least two cameras in the plurality of cameras to find a location of an inventory event in three dimensions in the area of real space. The system matches the location of the inventory event with an inventory location.

Abstract: Approaches provide for recognizing and locating text represented in image data. For example, image data that includes representations of text can be obtained. A width-focused recognition engine can be configured to analyze the image data to determine a base-set of words. The base-set of words can be associated with logical structure information that describes a geometric relationship between words in the base-set of words. A set of bounding boxes that includes one or more base words can be determined, as well as a confidence value for each base word. A depth-focused recognition engine can be configured to analyze the image data to determine a focused-set of words, the focused-set of words associated with a set of bounding boxes and confidence values for respective words. A set of merged words can be determined from a set of overlapping bounding boxes that overlap a threshold amount.

Abstract: An exemplary system according to various examples receives a function call including a plurality of operands, each operand in the plurality of operands comprising a set of data elements. The system identifies a plurality of actions associated with the function call and the plurality of operands, determines a set of dependencies among the plurality of actions for executing the actions using a set of computing resources, and presents the set of actions and the determined set of dependencies.

Abstract: A computerized system for recursively detecting anomalies in monitored behavior of entities. The system comprises a storage unit to store monitored events, event deviations and parameters related to each event and to each event deviation. The system comprises a processing unit configured to receive a plurality of input events, construct a plurality of baseline models, receive an input event that occurred during an analyzed timeframe, compare parameters of the received input event to a corresponding baseline model in order to detect an event deviation, and associate an event deviation score to the detected event deviation. Using the detected event deviation as an input event, said operations are repeated until a predetermined condition is satisfied, and an alert is generated, indicating suspicious activity has been detected. A viewer application configured to receive and display alerts relating to the detected event deviation is provided.

Abstract: Models are generated from objects identified in video. Each model is evaluated based on knowledge of the objects determined from video analysis, and preferred models are identified based on the evaluations. In some examples, each model could be evaluated by tracking a movement of each object in the video by using each model to track the object from which it was generated, evaluating an ability of each model to identify the objects in the video that are similar to the object from which it was generated, and determining an amount of false identifications made by each model of different objects in different video that does not include the object from which it was generated.

Abstract: System and method for tracking a mobile device includes: receiving unique identifications for a mobile device; filtering out the unique identifications to obtain a true identifications for the mobile device; identifying cameras relevant to movement of the mobile device; receiving video streams; generating data structures for the video streams and tracking information of the mobile device, the data structure including time stamped videos, and viewpoints of the identified cameras; utilizing the data structures to retrieve, video and tracking information for the mobile device and the user, as the mobile moves in the site; and applying analytics to the retrieved video and tracking information to analyze behavior of the user and to predict what the user will do while on site.

Abstract: A graphical user interface showing relevant sliding scale cluster groups having a processor generating a ranking of Top N1 features of the seed dataset in order of frequency of their occurrence. The processor generates another ranking of Top N2 features of the seed dataset in order of frequency of their occurrence in correlation with their equivalent percentage in total dataset. The Top M co-related features is identified for each of the Top N (N1+N2) features that are present for the seed dataset. The processor, for each one in M×N set, generates a sliding scale cluster via permutation of Top M features. The processor sorts each permutation based on closest occurrence match. The Seed Group Meta Bitmap Index is generated for the seed audience segment. For each cluster, the processor calculates the available amplification count from the Total Audience Bitmap Index, until the desired amplification is achieved.

Abstract: A system comprising a non-transient computer-readable storage medium having stored thereon instructions and at least one hardware processor configured to execute the instructions, to receive a video sequence; divide the video sequence into one or more scenes based on scene boundaries, wherein each scene comprises a plurality of temporally-contiguous image frames, and wherein said scene boundaries are being determined based on a similarity metric between two temporally-contiguous image frames meeting a dissimilarity threshold; and, for each scene of the one or more scenes, (i) generate a plurality of preliminary classifications of an object appearing in at least some of said image frames in the scene, wherein each of said plurality of preliminary classifications has a confidence score, and (ii) calculate a combined classification of the object based on said plurality of preliminary classifications, wherein each of said preliminary classifications is weighted in accordance with its confidence score.

Abstract: Embodiments of the present invention include multi-sensory stereo vision sensors suitable for use in robotics, navigation, machine vision, manufacturing, and other applications. In some cases, a sensor includes a stereo camera that produces image data for use in generating disparity maps to determine the positions of objects in the scene and/or the position of the sensor itself. The stereo sensor may include image sensors that are fastened to a unitary frame to prevent undesired drift and a thermal pad that wicks heat away from a processor. The processor may provide an efficient means to directly compute stereo disparity maps onboard the sensor. A sensor can also include a laser rangefinder that provides range data suitable for calibrating the stereo camera and for improving its accuracy in certain environments. In some cases, the laser is coupled to a spindle, which in turn is driven by a geartrain through a slipping clutch.

Abstract: Implementations relate to automatic response suggestions based on images received in messaging applications. In some implementations, a computer-executed method includes detecting a first image included within a first message received at a second device over a communication network from a first device of a first user, and programmatically analyzing the first image to extract a first image content. The method includes retrieving a first semantic concept associated with the first image content, programmatically generating a suggested response to the first message based on the first semantic concept, and transmitting instructions causing rendering of the suggested response in the messaging application as a suggestion to a second user of the second device.

Abstract: A method for training an automated classifier of input images includes: receiving, by a processing device, a convolution neural network (CNN) model; receiving, by the processing device, training images and corresponding classes, each of the corresponding classes being associated with several ones of the training images; preparing, by the processing device, the training images, including separating the training images into a training set of the training images and a testing set of the training images; and training, by the processing device, the CNN model utilizing the training set, the testing set, and the corresponding classes to generate the automated classifier.

Abstract: Systems and methods for training semantic segmentation. Embodiments of the present invention include predicting semantic labeling of each pixel in each of at least one training image using a semantic segmentation model. Further included is predicting semantic boundaries at boundary pixels of objects in the at least one training image using a semantic boundary model concurrently with predicting the semantic labeling. Also included is propagating sparse labels to every pixel in the at least one training image using the predicted semantic boundaries. Additionally, the embodiments include optimizing a loss function according the predicted semantic labeling and the propagated sparse labels to concurrently train the semantic segmentation model and the semantic boundary model to accurately and efficiently generate a learned semantic segmentation model from sparsely annotated training images.

Abstract: There is provided an apparatus for interpolating a lesion area when diagnosis is performed in a Computer Aided Diagnosis (CAD) system using consecutive images. According to an example, the apparatus includes: an image receiver configured to receive images sequentially; an image matcher configured to match a current image with reference images, and to determine whether to interpolate a lesion area in the current image based on a matching result; and a lesion area acquirer configured to interpolate or acquire the lesion area in the current image according to a result of the determination.

Abstract: The present invention provides a pixel array comprising a plurality of pixel units, each of which comprises three sub-pixels in different colors, wherein, in each pixel unit, any two adjacent sub-pixels are combined into a pixel block. Compared to the prior art, the width of the sub-pixel in the present invention increases, which reduces the difficulty of the manufacturing process of the pixel array and improves product yield. The present invention further provides a driving method of the pixel array, a display panel including the pixel array, and a display device including the display panel. When driving the above pixel array with the driving method, granular sensation of the display panel including the pixel array can be reduced, and a display effect of a display panel with higher resolution in the same size can be achieved.

Abstract: An exemplary system according to various examples receives a function call including a plurality of operands, each operand in the plurality of operands comprising a set of data elements. The system identifies a plurality of actions associated with the function call and the plurality of operands, determines a set of dependencies among the plurality of actions for executing the actions using a set of computing resources, and presents the set of actions and the determined set of dependencies.

Abstract: A segmentation platform is interposed between an intake server and remote user-accessible computers. The segmentation platform may include a model training computer processor configured to generate a predictive model for determining a segment corresponding to received data sets based upon claim segment rules and historical data sets stored in data storage devices. The segmentation platform may be configured to dynamically update workload data corresponding to a plurality of users, and responsive to that updating and based upon application of the predictive model, segment the received current data sets and transmit electronic claim files to respective remote user-accessible computing devices. The predictive model is continually adapted through activation of the model training component to update the predictive model with new current claim data sets.

Abstract: A method is provided to diagnose one or more malfunctions in a virtual network having a network functionality implemented in a distributed manner by hypervisors, each performing part of the network functionality. The method includes receiving user input of observed facts about the virtual network, where the observed facts include identifiers of virtual components in the virtual network, and adding the observed facts to a knowledge base. The method further includes, in response to the identifiers of the virtual components, querying agents on the hypervisors for collected facts related to the virtual components, receiving and adding the collected facts to the knowledge base, and applying logic rules to the knowledge base to produce one or more diagnoses of the virtual network.

Abstract: Embodiments relate to characterizing a water flow. Initially, a camera targeted at the water flow obtains images. An image pyramid is generated for each image, and a first level of each image pyramid is tiled at an initial scale to identify initial features. The initial features are matched across the first level of the image pyramids at a pixel-level to obtain a first set of feature displacements. A second level of each image pyramid is tiled at a decreased scale to identify a scaled set of features. The scaled features are matched across the second level of the image pyramids at the pixel-level to obtain a second set of feature displacements. Optical flow algorithms are applied to modify each feature displacement to account for a corresponding subpixel registration. A stereo reconstruction is applied to the feature displacements to generate a three dimensional (3D) displacement map.

Abstract: An image processing device includes a processor including hardware. The processor implements an image acquisition process that acquires time-series images that were captured in time series, and a process that detects a change position, the change position being a position at which an object captured within the time-series images changes from a first object to a second object. The processor implements the process that extracts a feature quantity from each of the time-series images, determines whether the object captured within each of the time-series images is the first object or the second object based on the feature quantity, extracts candidate positions for the change position based on the determination results, and compares the candidate positions based on the determination results to determine the change position.

Abstract: Methods and systems may help to provide filtered notification content that provides useful information to the intended recipient, but does not provide the same information to an unauthorized viewer. To do so, when an application event occurs, filtered notification content may be generated. The filtered notification content may combine a non-obfuscated portion of the event content and an obfuscated portion of the event content, such that when viewed by an intended recipient, the filtered notification content provides implicit information that the device expects the particular user to understand based on the user's own experience and/or other factors.

Abstract: An image recognition accelerator, a terminal device, and an image recognition method are provided. The image recognition accelerator includes a dimensionality-reduction processing module, an NVM, and an image matching module. The dimensionality-reduction processing module first reduces a dimensionality of first image data. The NVM writes, into a first storage area of the NVM according to a specified first current I, ? low-order bits of each numeric value of the first image data on which dimensionality reduction has been performed, and writes, into a second storage area of the NVM according to a specified second current, (N??) high-order bits of each numeric value of the first image data on which dimensionality reduction has been performed. The image matching module determines whether an image library stored in the NVM includes image data matching the first image data on which dimensionality reduction has been performed.

Abstract: In order to decrease a memory footprint for volume rendering, distance field information is adaptively compressed and merged with an existing data structure having unused memory to form a merged dataset. During rendering, the merged dataset is sampled, and a sampled value is used to identify a look-up table for a corresponding voxel or is decompressed and used to skip empty space.