Abstract: A method, apparatus and system for visual localization includes extracting appearance features of an image, extracting semantic features of the image, fusing the extracted appearance features and semantic features, pooling and projecting the fused features into a semantic embedding space having been trained using fused appearance and semantic features of images having known locations, computing a similarity measure between the projected fused features and embedded, fused appearance and semantic features of images, and predicting a location of the image associated with the projected, fused features. An image can include at least one image from a plurality of modalities such as a Light Detection and Ranging image, a Radio Detection and Ranging image, or a 3D Computer Aided Design modeling image, and an image from a different sensor, such as an RGB image sensor, captured from a same geo-location, which is used to determine the semantic features of the multi-modal image.

Abstract: A security system (10) includes an image information acquisition unit (11) that acquires input image information on an image taken of a person in a store, a tracking unit (12) that tracks an action of a hand of the person based on the input image information, and a suspicious action detection unit (13) that detects a suspicious action of the person based on the tracked action of the hand. A security system, a security method, and a security program capable of accurately detecting a suspicious action are thereby provided.

Abstract: An image processing system and related method. The system comprises an input interface (IN) configured for receiving an input image. A filter (FIL) of the system filters said input image to obtain a structure image from said input image, said structure image including a range of image values. A range identifier (RID) of the system identifies, based on an image histogram for the structure image, an image value sub-range within said range. The sub-range being associated with a region of interest. The system output through an output interface (OUT) a specification for said image value sub-range. In addition or instead, a mask image for the region of interest or for region or low information is output.

Abstract: A system for computer-aided triage includes and/or interfaces with a computing system. A method for computer-aided triage includes receiving a data packet including a set of images; and processing the set of images to determine a suspected condition and/or associated features. Additionally or alternatively, the method can include any or all of: preprocessing the set of images; triggering an action based on the suspected condition and/or associated features; determining a recipient based on the suspected condition; preparing a data packet for transfer; transmitting information to a device associated with the recipient; receiving an input from the recipient and triggering an action based on the input; aggregating data; and/or any other suitable processes.

Abstract: A processing for a first pixel in a picture comprises setting upper and/or lower limits of a first color component of the first pixel in a first color space to a respective fixed value if a maximum and/or minimum value of the first color component in the first color space results in a color component in a second color space that is below a first value of the color component in the second color space and above a second value of the color component in the second color space. A filtered value is obtained of the first color component and which is equal to or larger than the lower limit and equal to or lower than the upper limit. The processing results in filtered values that are cheaper to encode but that are visibly undistinguishable from the original colors of the pixels.

Abstract: Embodiments are described for detecting optical discrepancies associated with image capture analyzing pixels in multiple images corresponding to common points of reference in a physical environment. In an embodiment, photometric error values are averaged over time to compute the mean error at each pixel. Once the estimate of the mean error has a sufficient number of updates above a specified value, the estimate is thresholded to provide a mask of any optical discrepancies occurring in the stereo pair of images. Applications include detecting optical discrepancies in images captured for use by a visual navigation system in guiding an autonomous vehicle (e.g., an unmanned aerial vehicle).

Abstract: One disclosed example provides a head-mounted device configured to control a plurality of light sources of a handheld object and acquire image data comprising a sequence of environmental tracking exposures in which the plurality of light sources are controlled to have a lower integrated intensity and handheld object tracking exposures in which the plurality of light sources are controlled to have a higher integrated intensity. The instructions are further executable to detect, via an environmental tracking exposure, one or more features of the surrounding environment, determine a pose of the head-mounted device based upon the one or more features of the surrounding environment detected, detect via a handheld object tracking exposure the plurality of light sources of the handheld object, determine a pose of the handheld object relative to the head-mounted device based upon the plurality of light sources detected, and output the pose of the handheld object.

Abstract: A method for ascertaining features in an environment of at least one mobile unit for implementation of a localization and/or mapping by a control unit. In the course of the method, sensor measurement data of the environment are received, the sensor measurement data received are transformed by an alignment algorithm into a cost function and a cost map is generated with the aid of the cost function, a convergence map is generated based on the alignment algorithm. At least one feature is extracted from the cost map and/or the convergence map and stored, the at least one feature being provided in order to optimize a localization and/or mapping. A control unit, a computer program, and a machine-readable storage medium are also described.

Abstract: A specific area detection device that detects a specific area in an imaging area based on a captured image includes: an estimation unit configured to estimate a plurality of points and a direction of a straight line connecting two predetermined points among the plurality of points from a captured image using a learning model created by learning about a specific area defined by a predetermined number of the points in an imaging area using a captured image for learning; and a detection unit configured to detect the specific area by classifying the plurality of points for each specific area based on the direction.

Abstract: Provided is an information processing apparatus, including: an estimation processing section that, on the basis of three-dimensional data and a first image feature value that are set and a second image feature value that is acquired from a captured image captured by a first imaging apparatus, estimates a position and attitude of the first imaging apparatus.

Abstract: A non-transitory computer-readable recording medium stores therein an examination assisting program that causes a computer to execute a process including: performing a site detecting process that uses an object detection technique on each of a plurality of ultrasound examination images taken of an examined subject by performing a scan on the examined subject; and displaying a site detection map in which a detection result of each of a plurality of sites included in the examined subject is kept in correspondence with the scan, on a basis of detection results from the site detecting process.

Abstract: A shape measurement device composes shape information indicating a three-dimensional shape of a subject based on normal information and distance information acquired for the subject. The normal and distance information are two-dimensional information and have a pixel structure corresponding to the two-dimensional image. The device acquires the normal and distance information, sets processing-target segment regions with respect to the two-dimensional image upon composition of the shape information of the subject, composes, for each of the segment regions, first shape information based on the normal information, composes, for each of the segment regions, second shape information acquired by changing the first shape information based on the distance information, and composes combined shape information indicating the three-dimensional shape of the subject by combining the second shape information for a plurality of the segment regions.

Abstract: Techniques related to improved continuous local 3D reconstruction refinement are discussed. Such techniques include constructing and solving per 3D object adjustment models in real time to generate a point cloud and/or updated camera parameters for each object adjustment model.

Abstract: In a feature extraction apparatus, a small region setter divides an object region set in a captured image into small regions smaller in size than the object region. A small region extractor extracts, from each small region, a small-region feature that has two or more feature parameters associated with the corresponding small region. A feature calculator calculates a product of a first feature representing the small-region feature of a first small region selected as a target region from the small regions, and a second feature representing the small-region feature of a second small region in the small regions, the second small region having a predetermined positional relationship with the first small region. The feature calculator obtains, based on the product of the first feature and the second feature, an image feature for the first small region as the target region.

Abstract: A moving image generation apparatus includes: circuitry to: capture images of a three-dimensional model using different values of a camera parameter of a virtual camera to generate captured images; calculate goodness-of-fit indices using the captured images as inputs, the goodness-of-fit indices each indicating a suitability of a corresponding captured image among the captured images; and generate camerawork that traces values of the camera parameter of the virtual camera, based on the calculated goodness-of-fit indices.

Abstract: A system, method, and computer-readable medium are disclosed for augmented reality detection of enterprise systems in a data center. An augmented reality view is captured of an enterprise system and objects of the enterprise system. Significant areas are detected of the enterprise. In the captured augmented reality view bounding boxes are added around the significant areas. Determination is performed of three-dimensional orientation of the significant areas. Depth of the signification areas is determined based on the three-dimensional orientation.

Abstract: A computer implemented method, device and computer program device are provided that obtain a panoramic video for a scene, with a coordinate system. The method, device and computer program product identify a point of interest (POI) from the scene within the panoramic video, and track a position of the POI within the panoramic video. The method, device and computer program product record POI position data in connection with changes in the position of the POI during the panoramic video. The method, device and computer program product support play back of the panoramic video and adjustment of the field of view based on the POI position data.

Abstract: A method for in-situ data acquisition comprises providing a mold, wherein at least a portion of the mold is transparent, inserting a liquid composite molding reinforcement into a cavity of the mold, injecting a fluid into the cavity of the mold, the fluid comprising a fluorescent dye, lighting the mold with an ultraviolet lighting source and capturing a plurality of images of a front portion of the fluid as the fluid advances within the cavity of the mold. Capturing the plurality of images of a front portion of the fluid may include advancing a camera along a camera track as the fluid advances within the cavity of the mold. A corresponding method and computer program product for processing images captured by the above method are also disclosed herein.

Abstract: An image processing device includes: an extraction unit which extracts, from image data taken by shooting a neighborhood of a vehicle, edge points that are to be used for detecting partition lines of a parking frame and whose edge intensity values are larger than an edge threshold value; and a correction unit which corrects the edge threshold value based on a density of the edge points extracted by the extraction unit.

Abstract: The responses of reviewers while reviewing a media composition are captured automatically using imagery and/or audio of the reviewers. The captured information is analyzed to extract response characteristics, such as emotions elicited in reviewers by the media composition. The results of the analysis are synchronized with the composition and fed back to the editor, who may use the emotion response results to influence further editing of the composition. Media composition tools integrate a synchronized representation of reviewers' response characteristics within a timeline display of the composition within the tool's user interface. Emotional responses of individual reviewers or aggregated responses of groups of reviewers may be displayed on reviewer response characteristics tracks within the timeline display.