A polarized event camera system includes: an event camera having a field of view centered around an optical axis, the event camera including an image sensor including a plurality of pixels, each pixel of the event camera operating independently and asynchronously and being configured to generate change events based on changes in intensity of light received by the pixel; and a rotatable linear polarizer aligned with the optical axis of the event camera, the rotatable linear polarizer having a polarization axis, the polarization axis of the rotatable linear polarizer being rotatable about the optical axis of the event camera.

Provided are an image processing apparatus and an image processing method that process a far-infrared image. The image processing apparatus includes a region extraction section, a modal transformation section, and a superimposition section. The region extraction section extracts a region of interest within a visible-light image captured by a visible-light camera. The modal transformation section receives an image of the region of interest within an infrared image captured by an infrared camera observing the same subject as the visible-light camera, and transforms the received image to a modal image. The superimposition section generates a presentation image by superimposing the modal image on the region of interest within the visible-light image. The modal transformation section transforms a far-infrared image of the region of interest to a modal image including an information modal familiar to humans by using, for example, a database and a conditional probability distribution.

When a user designates a region of interest for a plurality of groups targeted for difference analysis in a microscopic observation image of a sample, an m/z candidate search unit searches for candidates for m/z presumed to differ, based on collected mass spectral data. An intensity histogram creation unit processing unit creates and displays a graph showing a frequency distribution of peak intensities at measurement points included in the ROI of the groups for each of the m/z candidates. If this graph exhibits multimodality, the data distribution is not suitable for a statistical hypothesis test. An intensity range determination unit limits an intensity range in accordance with a user's instruction. Then, ROI correction unit corrects the ROI so as to include only measurement points with peak intensities within the limited intensity range. A test processing unit performs a statistical hypothesis test using the data corresponding to the corrected ROI.

The current document is directed to automated methods and systems, controlled by various constraints and parameters, that identify contours in digital images, including curved contours. Certain of these parameters constrain contour identification to those contours in which the local curvature of a contour does not exceed a threshold local curvature and to those contours orthogonal to intensity gradients of at least threshold magnitudes. The currently described methods and systems identify seed points within a digital image, extend line segments from the seed points as an initial contour coincident with the seed point, and then iteratively extend the initial contour by adding line segments to one or both ends of the contour. The identified contours are selectively combined and filtered in order to identify a set of relevant contours for use in subsequent image-processing tasks.

A map creation apparatus includes an image receiver configured to receive images in time series while moving; a first calculator configured to extract an image area indicating an object from the images and calculate a coordinate of the object in a world coordinate system; a second calculator configured to track the object in the extracted image area with the images and calculate an optical flow of the object; an eliminator configured to calculate a difference in coordinate between vanishing points generated by the movement of the image receiver and the object based on the optical flow, and eliminate the image area of the object from the images when determining the object as a moving object based on the calculated difference; and a storage controller configured to store map information including the coordinate of the object, not eliminated by the moving object eliminator, in the world coordinate system.

An apparatus and method to adjust item recommendations are disclosed herein. A first image attribute of a query image is compared to a second image attribute of each of a plurality of inventory images of a plurality of inventory items to identify the inventory items similar to the query image. Item recommendations comprising the identified inventory items in a first listing order are provided for display at a remote device. A second listing order of the identified inventory items is determined based on a user preference for a particular one of the identified inventory items. At least the second listing order is provided to the remote device for re-display of the item recommendations in accordance with the second listing order.

Methods and apparatus, including computer program products, implementing and using techniques for detecting astronomical objects. An image frame is received, which includes representations of one or more astronomical objects. The received image frame is divided into several swaths. One or more swaths are selected, which include full or partial representations of one or more astronomical objects. Each of the one or more swaths and each astronomical object represented within the one or more swaths can be designated by a base-limit pair. The base-limit pairs for the selected one or more swaths are compared with base-limit pairs for one or more corresponding swaths using a difference algorithm. A list of differences in the base-limit pairs is created.

A method includes receiving first data defining a first bounding box for a first image of a sequence of images. The first bounding box corresponds to a region of interest including a tracked object. The method also includes receiving object tracking data for a second image of the sequence of images, the object tracking data defining a second bounding box. The second bounding box corresponds to the region of interest including the tracked object in the second image. The method further includes determining a similarity metric for first pixels within the first bounding box and search pixels within each of multiple search bounding boxes. Search coordinates of each of the search bounding boxes correspond to second coordinates of the second bounding box shifted in one or more directions. The method also includes determining a modified second bounding box based on the similarity metric.

Techniques describe computing computer vision (CV) features based on sensor readings from a sensor and detecting macro-features based on the CV features. The sensor may include a sensor element array that includes a plurality of sensor elements. The sensor may also include in-pixel circuitry coupled to the sensor elements, peripheral circuitry and/or a dedicated microprocessor coupled to the sensor element array. The in-pixel circuitry, the peripheral circuitry or the dedicated microprocessor may include computation structures configured to perform analog or digital operations representative of a multi-pixel computation for a sensor element (or block of sensor elements), based on sensor readings generated by neighboring sensor elements in proximity to the sensor element, and to generate CV features. The dedicated microprocessor may process the CV features and detect macro-features. Furthermore, in certain embodiments, the dedicated microprocessor may be coupled to a second microprocessor through a wired or wireless interface.

A system of identifying one or more fillable fields of an electronic form may include an electronic device, and a computer-readable storage medium that includes one or more programming instructions. The programming instructions are configured to instruct the electronic device to receive an electronic form, identify fillable field candidates of the electronic form, and determine, for each fillable field candidate, whether the fillable field candidate is a fillable field. The system updates metadata associated with the electronic form by applying a sequencing framework to only the fillable fields by obtaining position information for each fillable field that indicates a position of the fillable field on the document, sorting the fillable fields based on the position information to form a sequence of fillable fields, determining a designator to each fillable field that indicates a position of a corresponding fillable field in the sequence, and storing the designator.