Abstract: A method of jitter detection and image restoration for high-resolution TDI CCD satellite images. The method includes: obtaining a parallax image after a sub-pixel matching method relying on a correlation coefficient and least squares algorithm; transferring a jitter offset from an image space to an object space by an integral transformation function (ITF); dealing with a continuous push-broom mode of cameras in a discrete way with a denser sampling strategy according to a continue dynamic shooting model (CDSM), obtaining a specialized CDSM and feeding it back to the ITF; applying the accurate ITF to the obtained parallax image and conducting the jitter curve fitting to achieve the jitter detection; estimating a correspondent partial PSF according to the CDSM and the obtained jitter curve; carrying out an adaptive restoration based on context through optimal window Wiener filtering, by means of multiple input and single output to completes the image restoration.

Abstract: The present invention is directed to making it possible to reduce a possibility of image stitching failures. An information processing apparatus includes a feature extraction unit configured to extract feature points from each of a plurality of images of an object to be inspected captured from a plurality of viewpoints, an image quality evaluation unit configured to, for each of the plurality of images, evaluate whether an image quality based on a predetermined index satisfies allowable conditions for inspection works of the object, and an image stitching unit configured to stitch at least a part of the images, among the plurality of images, having the image quality that satisfies the allowable conditions according to a positional relation based on the feature points.

Abstract: An image style transform method includes: acquiring an initial image to be subjected to style transform; inputting a gradient of the initial image to an image style transform model, and obtaining a feature map of the initial image in a gradient domain from the image style transform model, where the image style transform model is obtained by being trained in the gradient domain based on a pixel-wise loss and a perceptual loss; and performing image reconstruction according to the feature map of the initial image in the gradient domain to obtain a style image.

Abstract: An information processing apparatus comprising, a first determination unit configured to determine whether a subject corresponding to a person is included in an input image, and a second determination unit configured to associate a first region corresponding to a first subject determined to be included in the input image by the first determination unit with a second region determined to include the first subject in one or more images input earlier than the input image, and to determine whether the first subject is to be included in a person detection result on the basis of a degree of a temporal change of feature amounts obtained from the first region and the second region, respectively.

Abstract: Embodiments of the present disclosure provide an image processing method and apparatus, a computer device and a computer readable storage medium. The method includes: in response to detecting that a number of images in an image set to be processed exceeds a preset threshold, acquiring a first cluster dimension corresponding to the images in the image set; selecting a second cluster dimension from a plurality of pre-stored dimensions, the second cluster dimension being different from the first cluster dimension; and clustering the images in the image set according to the second cluster dimension to acquire a plurality of first image subsets of the image set.

Abstract: An image processing system enables a user wearing a head-mounted display to experience a virtual environment combined with a representation of a real-world object. The image processing system receives a captured scene of a real-world environment that includes a target object. The image processing system identifies the target object in the captured scene and generates a representation of the target object. In some cases, the image processing system may include a graphical overlay with the representation of the target objet. The image processing system can generate a combined scene that includes the target object and the virtual environment. The combined scene is presented to the user, thereby allowing the user to interact with the real-world target object (or a representation thereof) in combination with the virtual environment.

Abstract: An object of the present invention is to achieve both suppression of data amount of an image processing system that learns a collation image to be used for image identification using a discriminator and improvement of identification performance of the discriminator. In order to achieve the above object, there is proposed an image processing system including a discriminator that identifies an image using a collation image, the image processing system further including a machine learning engine that performs machine learning of collation image data required for image identification. The machine learning engine searches for a successfully identified image using an image for which identification has been failed, and adds information, obtained based on a partial image of the image for which identification has been failed and which has been selected by an input device to the successfully identified image obtained by the search to generate corrected collation image data.

Abstract: A device and method for recognizing an object included in an input image are provided, the device for recognizing the object included in the input image includes a memory in which at least one program is stored; a camera configured to capture an environment around the device; and at least one processor configured to execute the at least one program to recognize an object included in an input image, wherein the at least one program includes instructions to: obtain the input image by controlling the camera; obtain information about the environment around the device that obtains the input image; determine, based on the information about the environment, a standard for using a plurality of feature value sets in a combined way, the plurality of feature value sets being used to recognize the object in the input image; and recognize the object included in the input image, by using the plurality of feature value sets based on the determined standard for using the plurality of feature value sets in the combined way.

Abstract: An information processing apparatus includes a processor configured to extract an annotated page and one or more associated pages associated with the annotated page from target data including plural pages.

Abstract: An occupant observation device includes an imager configured to capture an image of a head of an occupant of a vehicle; an eye detector configured to detect at least a part of eyes of the occupant in an image captured by the imager; a mouth detector configured to detect at least a part of the mouth of the occupant in the image captured by the imager; and a condition estimator configured to estimate a condition of the occupant on the basis of a detection result of the eye detector and a detection result of the mouth detector, in which the condition estimator changes a ratio of reflecting each of the detection result of the eye detector and the detection result of the mouth detector in an estimation of the condition of the occupant, on the basis of the detection result of the eye detector or a result of a process performed on the basis of the detection result of the eye detector.

Abstract: Systems and methods are described for determining that the user interaction with a display of a computing device during display of a video comprising a sequence of frames indicates a region of interest in a current frame of the sequence of frames of the displayed video. For each frame of the sequence of frames after the current frame, the frame is cropped to generate a cropped frame comprising a portion of the frame including the region of interest in the frame, the cropped frame is enlarged based on a display size corresponding to an angle or orientation of the computing device during display of the video, and the enlarged cropped frame replaces the frame such that the enlarged cropped frame is displayed in the sequence of frames of the video on the display of the computing device instead of the frame.

Abstract: Embodiments of this application disclose a position and attitude determining method. The method includes acquiring, by tracking a feature point of a first marked image, position and attitude parameters of an image captured by a camera; using a previous image of a first image as a second marked image in response to the previous image of the first image meeting a feature point tracking condition and the first image failing to meet the feature point tracking condition; acquiring, position and attitude parameters of the image captured by the camera relative to the second marked image; acquiring position and attitude parameters according to the position and attitude parameters of the image relative to the second marked image and position and attitude parameters of each marked image relative to a previous marked image; and determining a position and an attitude of the camera according to the position and attitude parameters.

Abstract: A method for acquiring queuing information includes: acquiring a location and a height of each pixel point in a first video image in a world coordinate system, wherein the first video image is a video image captured by a video camera at a queue area; determining a behavior state of each human body at the area based on the location and the height of each pixel point; and acquiring queuing information based on the behavior state of each human body at the area at a current time.

Abstract: The present invention enables the automatic generation and recommendation of embedded images. An embedded image includes a visual representation of a context-appropriate object embedded within a scene image. The context and aesthetic properties (e.g., the colors, textures, lighting, position, orientation, and size) of the visual representation of the object may be automatically varied to increase an associated objective compatibility score that is based on the context and aesthetics of the scene image. The scene image may depict a visual representation of a scene, e.g., a background scene. Thus, a scene image may be a background image that depicts a background and/or scene to automatically pair with the object. The object may be a three-dimensional (3D) physical or virtual object. The automatically generated embedded image may be a composite image that includes at least a partially optimized visual representation of a context-appropriate object composited within the scene image.

Abstract: A device includes an image data receiving component, a vegetation index generation component, a crop data receiving component, a masking component and a multivariate regression component. The image data receiving component receives image data of a geographic region. The vegetation index generation component generates an array of vegetation indices based on the received image data, and includes a plurality of vegetation index generating components, each operable to generate a respective individual vegetation index based on the received image data. The crop data receiving component receives crop data associated with the geographic region. The masking component generates a masked vegetation index based on the array of vegetation indices and the received crop data. The multivariate regression component generates a crop parameter based on the masked vegetation index.

Abstract: An object identification method is disclosed. The method includes obtaining images of a target geographical area and telemetry information of an image-collection vehicle at a time of capture, analyzing each image to identify objects, and determining a position of the objects. The method further includes determining an image capture height, determining a position of the image using the capture height and the telemetry information, performing a transform on the image based on the capture height and the telemetry information, identifying the objects in the transformed image, determining first pixel locations of the objects within the transformed image, performing a reverse transform on the first pixel locations to determine second pixel locations in the image, and determining positions of the objects within the area based on the second pixel locations within the captured image and the determined image position.

Abstract: An image processing device includes: an extraction unit configured to extract at least one edge line based on image data obtained by an imaging device configured to capture a surrounding of a vehicle; a giving unit configured to give a priority to each of the at least one edge line; a registration unit configured to register the at least one edge line in descending order of the priority while limiting a number of registration of the at least one edge line to an upper limit or smaller of the number of registration; and a detection unit configured to detect a parking space, based on the at least one edge line registered.

Abstract: Methods of measuring variation across multiple instances of a pattern on a substrate or substrates after a step in a device manufacturing process are disclosed. In one arrangement, data representing a set of images is received. Each image represents a different instance of the pattern, wherein the pattern includes a plurality of pattern elements. The set of images are registered relative to each other to superimpose the instances of the pattern. The registration includes applying different weightings to two or more of the plurality of pattern elements, wherein the weightings control the extent to which each pattern element contributes to the registration of the set of images and each weighting is based on an expected variation of the pattern element to which the weighting is applied. Variation in the pattern is measured using the registered set of images.

Abstract: Systems and methods are described for determining that the user interaction with a display of a computing device during display of a video comprising a sequence of frames indicates a region of interest in a current frame of the sequence of frames of the displayed video. For each frame of the sequence of frames after the current frame, the frame is cropped to generate a cropped frame comprising a portion of the frame including the region of interest in the frame, the cropped frame is enlarged based on a display size corresponding to an angle or orientation of the computing device during display of the video, and the enlarged cropped frame replaces the frame such that the enlarged cropped frame is displayed in the sequence of frames of the video on the display of the computing device instead of the frame.

Abstract: A character recognition method for a moving image includes extracting a region corresponding to a character string included in each frame of a moving image to be recognized. The method reads a character string from the extracted region and corrects the character string read from each frame, based on appearance rule information that specifies an appearance rule of a character string corresponding to the order of the frames, such that the appearance order of the read character string conforms to the appearance rule.

Abstract: Disclosed herein is an artificial intelligence apparatus for recognizing at least one object, comprising: a memory configured to store a plurality of recognition models for generating identification information corresponding to the object from image data; and a processor configured to: obtain image data for the object, generate first identification information corresponding to the object from the image data using a default recognition model composed of at least one or more of the plurality of recognition models, measure a confidence level for the first identification information, obtain the first identification information as a recognition result of the object if the confidence level is equal to or greater than a first reference value, and obtain second identification information corresponding to the object from the image data as a recognition result of the object using a compound recognition model composed of at least one or more of the plurality of recognition models if the measured confidence level is less

Abstract: Described are systems and methods for generating training data that is used to train a machine learning system to detect moving objects represented in sensor data. The system and methods utilize position data received from a target vehicle to determine data points within sensor data that represents that target vehicle. For example, a station at a known location may receive Automatic Dependent Surveillance-Broadcast (“ADS-B”) data (position data) corresponding to a target vehicle that is within the field of view of a station sensor, such as a camera. The position data may then be correlated with the sensor data and projected into the sensor data to determine data points within the sensor data that represent the target vehicle. Those data points are then labeled to indicate the location, size, and/or shape of the target vehicle as represented in the sensor data, thereby producing training that may be provided to train a machine learning algorithm or system to detect moving objects, such as aircraft.

Abstract: Systems and methods for implementing radial density masking graphics rendering for use in applications such as head mounted displays (“HMDs”) are described. Exemplary algorithms are disclosed, according to which image resolution varies within an image depending on the distance of a particular point on the image from one or more fixation points. Reconstruction algorithms according to certain embodiments include three stages: (1) hole filling; (2) cross-cell blending; and (3) Gaussian blur.

Abstract: A method includes: receiving initial input from a client at least partially specifying one or more characteristics sought by the client; selecting a set of images from an image database for output to the client; and determining after each set of images whether an end condition has occurred. The method also includes, until the end condition has occurred: responsive to each set of images output to the client, receiving additional input from the client further specifying the one or more characteristics sought by the client; and responsive to each input received from the client, selecting another set of images for presentation to the client, said set of images being determined to at least partially satisfy the one or more characteristics specified by all input received from the client, said determination being based at least in part on side information for respective images for at least the set of images.

Abstract: A system performs optical character recognition (OCR) on an image displaying a portion of an object. An image classification system identifies the object in the image, based on which one or more object detection models identify labels associated with the object within the image. The system determines text of the identified labels using OCR, and analyzes the OCR resultant text for discrepancies and/or inaccuracies. In response to identifying a discrepancy, the system provides a recommendation for improving the accuracy of the OCR resultant text.

Abstract: In one embodiment, a method includes receiving a query comprising a query content object and constraints, generating a feature vector representing the query content object, accessing a sparse graph comprising nodes corresponding to candidate content objects represented by compact codes and links connecting the nodes, selecting an entry node, selecting similar content objects iteratively by identifying linked nodes of the entry node, decompressing the compact codes representing candidate content objects to generate feature vectors, selecting zero or more similar content objects based on a comparison between the feature vector representing the query content object and the feature vectors representing the candidate content objects, returning the selected similar content objects if a completion condition is satisfied, else repeating the iterative selection by using a linked node corresponding to a most similar content object as the entry node, and sending instructions for presenting one or more of the selected si

Abstract: A hand interaction system can use a three-state model to differentiate between normal hand movements, such as reaching for an object, and hand input gestures. The three-state model can specify a sequence of states including: 1) a neutral state, 2) a tracking state, and 3) an active state. In the neutral state, the hand interaction system monitors for a gesture signaling a transition to the tracking state but does not otherwise interpret a gesture corresponding to the active state as input. Once a gesture causes a transition to the intermediate tracking state, the hand interaction system can recognize a further active state transition gesture, allowing active state interaction. Thus, the monitoring for the intermediate tracking state provides a gating mechanism, making it less likely that the hand interaction system will interpret hand movements as input when not so intended by the user.

Abstract: An image processing apparatus and method thereof are provided. The image processing apparatus stores at least a reference image and performs the following operations: (a) receiving an image, (b) determining a plurality of representative keypoints for the image, such as determining the representative keypoints by a density restriction based method, (c) finding out that a matched area in the image corresponds to a first reference image according to the representative keypoints, (d) determining that a matched number between the representative keypoints and a plurality of reference keypoints of the first reference image is less than a threshold, and (e) storing the matched area in the image processing apparatus as a second reference image.

Abstract: Generally discussed herein are devices, systems, and methods for privacy-preserving video. A method can include identifying which classes of objects are present in video data, for each class of the classes identified in the video data, generating respective video streams that include objects of the class and exclude objects not of the class, and providing each of the respective video streams to a content distribution network.

Abstract: A management system includes: an information storage member that stores individual identification information of a management target; an information reading device that reads individual identification information I from the information storage member located within a predetermined distance from the information reading device; an imaging device hat generates continuous image data by continuously capturing images of at least an area where the information reading device can read the individual identification information I from the information storage member; a storage device that stores the continuous image data; a control device that acquires an event occurrence time at which an event related to the individual identification information I read by the information reading device has occurred, and sets in the continuous image data a playback start time corresponding to the event occurrence time; and a display device capable of displaying an image based on the continuous image data.

Abstract: An image processing device includes a control unit configured to control generation of a parameter related to adjustment of color corresponding to mutually different exposure times on the basis of a plurality of images photographed at the exposure times.

Abstract: Provided is an occupant observation device including an imager configured to capture an image of a head of an occupant of a vehicle; and an eye detector configured to detect at least a part of eyes of the occupant in the image captured by the imager, in which the eye detector sets an eye closer to the imager among the eyes of the occupant as a detection target.

Abstract: The present disclosure relates to a system and a method for identification of individual animals based on images, such as 3D-images, of the animals, especially of cattle and cows. When animals live in areas or enclosures where they freely move around, it can be complicated to identify the individual animal. In a first aspect the present disclosure relates to a method for determining the identity of an individual animal in a population of animals with known identity, the method comprising the steps of acquiring at least one image of the back of a preselected animal, extracting data from said at least one image relating to the anatomy of the back and/or topology of the back of the preselected animal, and comparing and/or matching said extracted data against reference data corresponding to the anatomy of the back and/or topology of the back of the animals with known identity, thereby identifying the preselected animal.

Abstract: Systems and methods for determining locations and configuring controllable devices are provided. Example systems and methods include determining a location estimate for a computing device and capturing image data, by the computing device, of a physical space that includes a controllable device performing an identification action. The example systems and methods may also include identifying the controllable device in the image data based at least in part on the identification action and determining configuration information for the controllable device. The configuration information may be based at least in part on the location estimate for the computing device.

Abstract: Example systems and methods may selection of video frames using a machine learning (ML) predictor program are disclosed. The ML predictor program may generate predicted cropping boundaries for any given input image. Training raw images associated with respective sets of training master images indicative of cropping characteristics for the training raw image may be input to the ML predictor, and the ML predictor program trained to predict cropping boundaries for raw image based on expected cropping boundaries associated training master images. At runtime, the trained ML predictor program may be applied to runtime raw images in order to generate respective sets of runtime cropping boundaries corresponding to different cropped versions of the runtime raw image. The runtime raw images may be stored with information indicative of the respective sets of runtime boundaries.

Abstract: There are disclosed various methods, apparatuses and computer program products for video encoding and decoding. In some embodiments a bitstream comprising a coded first-view picture and a coded second-view picture is encoded or encapsulated. The coded second-view picture represents a smaller field of view than the coded first-view picture, wherein decoding of the coded first-view picture results in a decoded first-view picture, and decoding of the coded second-view picture results in a decoded second-view picture. An indication is inserted in or along the bitstream that a reconstructed second-view picture comprises the decoded second-view picture and at least one region of the decoded first-view picture, wherein the reconstructed second-view picture represents the same field of view as the decoded first-view picture.

Abstract: Aspects of the disclosure provide for mechanisms for identification of table partitions in documents using neural networks. A method of the disclosure includes obtaining a plurality of symbol sequences of a document having at least one table, determining a plurality of vectors representative of symbol sequences having at least one alphanumeric character or a table graphics element, processing the plurality of vectors using a first neural network to obtain a plurality of recalculated vectors, determining an association between a first recalculated vector and a second recalculated vector, wherein the first recalculated vector is representative of an alphanumeric sequence and the second recalculated vector is associated with a table partition, and determining, based on the association between the first recalculated vector and the second recalculated vector, an association between the alphanumeric sequence and the table partition.

Abstract: Disclosed herein is a learning method of a neural network model for flame determination. The learning method of a neural network includes generating a learning image including a fake image generated by combining a real fire image and an arbitrary flame image with a background image; inputting the learning image to a first neural network model and outputting a determination result for whether a flame is present; and updating a weight in a layer extracting features of the learning image from the first neural network model using the determination result. According to the present invention, data of various fire situations may be secured, a performance of the neural network model that determines an occurrence of the fire through the secured data may be increased, and a quality of data for learning may be increased to allow the neural network model itself to predict various situations of fires.

Abstract: A disclosed image processing apparatus calculates a background vector expressing a motion of a background based on a plurality of motion vectors detected between a plurality of images. Then the image processing apparatus detects a motion vector of a moving object from the plurality of motion vectors, based on a magnitude of Euclidean distance between each of the plurality of motion vectors and the background vector.

Abstract: Systems and methods including one or more processing modules and one or more non-transitory storage modules storing computing instructions configured to run on the one or more processing modules and perform acts of obtaining a uniform resource locator (URL) of a first webpage that is shown on a graphical user interface and that is external to a website of a retailer (where, in some embodiments, the URL is obtained from a referral website or is entered by a user from a chat window or search box), using a web scraper to extract web text displayed on the first webpage on the graphical user interface, processing the web text displayed on the first webpage on the graphical user interface to determine an interest of a user, using a set of rules to determine items related to the web text displayed on the first webpage on the graphical user interface, and coordinating displaying the items on a second webpage to promote the items as related to the interest of the user, where the second webpage is internal or external

Abstract: Disclosed is a method for selecting a cosmetic product, and a method for image acquisition and image processing for the selection method, including: acquiring an image of a person in a controlled lighting environment, and measuring and recording the colorimetric coordinates of the person's face; processing the image to determine an absolute value of the skin tone; correlating the absolute value with a usage color map established for each of multiple cosmetic products of a database by measuring the color of each cosmetic product under its conditions of use, and to determine a personalized color matrix; extracting, from the database, the cosmetic product(s) whose color measurement is part of the personalized color matrix; using an information medium, presenting the product(s) included in the personalized color matrix; and optionally selecting the preferred product(s) chosen by the person from those that are part of the personalized color matrix.

Abstract: Methods, devices, computer readable medium, and systems are described for capturing images at venues. Venues are organized around one or more shotspots. Shotspots are geographic locations which may have one or more subspots and one or more venue operated camera devices. Subspots identify positions to be occupied by subjects within a shotspot. Shotspots are installed, registered, and operated by venue operators. Images are captured based on triggers which may include one or more conditions under which images will be stored. Conditions may also include negative limitations. Users wishing to use a shotspot do so through a mobile device. Interacting through the mobile device, a user may discover, receive directions to, navigate to, and arrange sessions during which they may use a shotspot. Users may also receive sample images, define triggers, initiate triggers, preview framing, and receive images through the mobile application.

Abstract: Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing a program and a method for synthesizing a realistic image with a new expression of a face in an input image by receiving an input image comprising a face having a first expression; obtaining a target expression for the face; and extracting a texture of the face and a shape of the face. The program and method for generating, based on the extracted texture of the face, a target texture corresponding to the obtained target expression using a first machine learning technique; generating, based on the extracted shape of the face, a target shape corresponding to the obtained target expression using a second machine learning technique; and combining the generated target texture and generated target shape into an output image comprising the face having a second expression corresponding to the obtained target expression.

Abstract: Systems, methods, and non-transitory computer-readable media can identify a set of videos. One or more overlapping portions in the set of videos are automatically identified. A stitched media content item is automatically generated based on the one or more overlapping portions and at least a subset of the set of videos.

Abstract: The present disclosure relates to systems and methods for image capture. Namely, an image capture system may include a camera configured to capture images of a field of view, a display, and a controller. An initial image of the field of view from an initial camera pose may be captured. An obstruction may be determined to be observable in the field of view. Based on the obstruction, at least one desired camera pose may be determined. The at least one desired camera pose includes at least one desired position of the camera. A capture interface may be displayed, which may include instructions for moving the camera to the at least one desired camera pose. At least one further image of the field of view from the at least one desired camera pose may be captured. Captured images may be processed to remove the obstruction from a background image.

Abstract: A method for determining a location of a target positioned behind a tow vehicle is provided. The method includes receiving images from a camera positioned on a back portion of the tow vehicle. The images include the target. The method includes applying one or more filter banks to the images. The method also includes determining a region of interest within each image based on the applied filter banks. The region of interest includes the target. The method also includes identifying the target within the region of interest and determining a target location of the target including a location in a real-world coordinate system. The method also includes transmitting instructions to a drive system supported by the vehicle. The instructions cause the tow vehicle to autonomously maneuver towards the location in the real-world coordinate system.

Abstract: A captured image acquisition section 50 acquires, from an imaging apparatus 12, data of a polarized image obtained by capturing a target object and stores the data into an image data storage section 52. A region extraction section 60 of a target object recognition section 54 extracts a region in which a figure of the target object is included in the polarized image. A normal line distribution acquisition section 62 acquires a distribution of normal line vectors on a target object surface in regard to the extracted region. A model adjustment section 66 adjusts a three-dimensional model of the target object stored in a model data storage section 64 in a virtual three-dimensional space such that the three-dimensional model conforms to the distribution of the normal line vectors acquired from the polarized image to specify a state of the target object.

Abstract: Provided is an occupant observation device including an imager configured to capture an image of a head of an occupant of a vehicle; and an eye detector configured to detect at least a part of eyes of the occupant in the image captured by the imager, in which the eye detector sets an eye closer to the imager among the eyes of the occupant as a detection target.

Abstract: A target identification method includes: using information of a to-be-detected target acquired within a predetermined time period as judgment information; acquiring an identification result of the to-be-detected target at a current time and outputting the identification result; judging whether the attribute type corresponding to the identification result is an attribute type having the highest priority; and if the attribute type corresponding to the identification result is not the attribute type having the highest priority, using information of the to-be-detected target acquired within a next predetermined time period as the judgment information, and returning to the step of acquiring an identification result of the to-be-detected target at a current time and outputting the identification result.

Abstract: Systems and methods for searching digital content, such as digital images, are disclosed. A method includes receiving a first search constraint and generating search results based on the first search constraint. A search constraint includes search values or criteria. The search results include a ranked set of digital images. A second search constraint and a weight value associated with the second search constraint are received. The search results are updated based on the second search constraint and the weight value. The updated search results are provided to a user. Updating the search results includes determining a ranking (or a re-ranking) for each item of content included in the search results based on the first search constraint, the second search constraint, and the weight value. Re-ranking the search results may further be based on a weight value associated with the first search constraint, such as a default or maximum weight value.