A method and system for logging and reporting on slow drivers in fast and middle lanes is disclosed. The system detects a slow vehicle in front of an automobile based on speed data from an OBD system, stores images of a rear of the slow vehicle using a forward facing video camera, detects passing of the slow vehicle on the left side of the automobile using a proximity sensor, stores images of a front of the slow vehicle using a rear facing video camera, after the automobile has passed the slow vehicle, stores global position data of the automobile using a GPS system, and transmits the speed data, the images of the rear of the slow vehicle, images of the front of the slow vehicle and the global position data that was taken and stored to the third party via the communications network, using the transmitter.

Provided herein are display systems and units, including those configured for dynamic communication in a physical location, such as in retail settings. Also included herein are methods for dynamically displaying product information in a physical location, such as a retail setting.

A reverse vending machine, including: a chamber adapted to receive an object returned to the reverse vending machine; a plurality of cameras arranged around the perimeter of the chamber for viewing said object; a transparent or translucent plate arranged such that the cameras in use view the object obliquely through the transparent or translucent plate; and means adapted to couple light into the plate such that the light undergoes total internal reflection in the plate. Also, a method of detecting dirt in a reverse vending machine.

A system for applying video data to a neural network (NN) for online multi-class multi-object tracking includes a computer programed to perform an image classification method including the operations of receiving a video sequence; detecting candidate objects in each of a previous and a current video frame; transforming the previous and current video frames into a temporal difference input image; applying the temporal difference input image to a pre-trained neural network (NN) (or deep convolutional network) comprising an ordered sequence of layers; and based on a classification value received by the neural network, associating a pair of detected candidate objects in the previous and current frames as belonging to one of matching objects and different objects.

An information processing device which processes information regarding a 3D model corresponding to a target object, includes a template creator that creates a template in which feature information and 3D locations are associated with each other, the feature information representing a plurality of 2D locations included in a contour obtained through a projection of the prepared 3D model onto a virtual plane based on a viewpoint, and the 3D locations corresponding to the 2D locations and being represented in a 3D coordinate system, the template being correlated with the viewpoint.

A system and a process are provided for evaluating subliminal pixel patterns and identifying trigger patterns, which are pixel patterns that trigger a response in subjects exposed to the pattern. Each pixel pattern is embedded in a digital video or a digital still image. Pixel patterns that are found to induce reactions in subjects are identified as trigger patterns and are flagged for re-testing. Re-tested trigger patterns that repeatably induce reactions are identified as positive trigger patterns and are studied further. Variations are made to a positive trigger pattern to determine whether small changes can affect how a subject responds when exposed to that positive trigger pattern. A positive trigger pattern is evaluated to determine whether it can induce an emotional, a physical, and/or a behavioral change in the subjects and, if so, the positive trigger pattern is applied to a real-world situation.

A method for controlling a light-field camera device includes controlling the light-field camera to capture a plurality of images. Situational measurements or markers of the light-field camera are recorded when the light-field camera captures each of the plurality of images, the plurality of images are composed into a three-dimensional image for composing and capturing a desired image.

An electronic keyboard using a camera, and more particularly, to an electronic keyboard using a camera, which includes a retroreflective film, a light source for irradiating light on to the retroreflective film, a camera for capturing light of a light source retroreflected from the retroreflective film, and an image processing means that analyzes the captured image to track the position of the reflected light source, to find a depressed state of the keyboard, and to generate a sound of an instrument corresponding to the depressed state.

In some arrangements, product packaging is digitally watermarked over most of its extent to facilitate high-throughput item identification at retail checkouts. Imagery captured by conventional or plenoptic cameras can be processed (e.g., by GPUs) to derive several different perspective-transformed views—further minimizing the need to manually reposition items for identification. Crinkles and other deformations in product packaging can be optically sensed, allowing such surfaces to be virtually flattened to aid identification. Piles of items can be 3D-modelled and virtually segmented into geometric primitives to aid identification, and to discover locations of obscured items. Other data (e.g., including data from sensors in aisles, shelves and carts, and gaze tracking for clues about visual saliency) can be used in assessing identification hypotheses about an item. Logos may be identified and used—or ignored—in product identification. A great variety of other features and arrangements are also detailed.

The invention relates to a method for detecting a phantom, comprising the steps of: arranging a phantom with respect to an object, acquiring at least one image of said object by means of an x-ray apparatus, such that the image contains projections of the object and projections of at least three first calibration fiducials of the phantom, detecting the projections of the at least three first calibration fiducials in said at least one image, and establishing a correspondence between the 2D image coordinates of said projections of the at least three first calibration fiducials and the 3D coordinates of said at least three first calibration fiducials in a local coordinate system of the phantom for computing the projection matrix at least up to a scale factor.