Abstract:
A method and system for filtering an image frame of a video sequence from spurious motion, comprising the steps of dividing the image frame and a preceding image frame of the video sequence into blocks of pixels; determining motion vectors for the blocks of the image frame; determining inter-frame transformation parameters for the image frame based on the determined motion vectors; and generating a filtered image frame based on the determined inter-frame transformation parameters; wherein the image frame is dived into overlapping blocks.
Abstract:
In accordance with an embodiment, a method of detecting moving objects via a moving camera includes receiving a sequence of images from the moving camera; determining optical flow data from the sequence of images; decomposing the optical flow data into global motion related motion vectors and local object related motion vectors; calculating global motion parameters from the global motion related motion vectors; calculating moto-compensated vectors from the local object related motion vectors and the calculated global motion parameters; compensating the local object related motion vectors using the calculated global motion parameters; and clustering the compensated local object related motion vectors to generate a list of detected moving objects.
Abstract:
Image processing circuitry processes image frames in a sequence of image frames, for example, to identify objects of interest. The processing includes filtering motion vectors associated with a current image frame, grouping the filtered motion vectors associated with the current image frame into a set of clusters associated with the current image frame, and selectively merging clusters in the set of clusters associated with the current image frame. At least one of the filtering, the grouping and the merging may be based on one or more clusters associated with one or more previous image frames in the sequence of image frames. Motion vectors included in merged clusters associated with a previous frame may be added to filtered motion vectors before grouping the motion vectors in the current frame.
Abstract:
A sequence of images obtained by a camera mounted on a vehicle is processed in order to generate Optical Flow data including a list of Motion Vectors being associated with respective features in the sequence of images. The Optical Flow data is analyzed to calculate a Vanishing Point by calculating the mean point of all intersections of straight lines passing through motion vectors lying in a road. An Horizontal Filter subset is determined taking into account the Vanishing Point and a Bound Box list from a previous frame in order to filter from the Optical Flow the horizontal motion vectors. The subset of Optical Flow is clustered to generate the Bound Box list retrieving the moving objects in a scene. The Bound Box list is sent to an Alert Generation device and an output video shows the input scene where the detected moving objects are surrounded by a Bounding Box.
Abstract:
An embodiment of a method for computing pyramids of input images (I) in a transformed domain, e.g., for search and retrieval purposes, includes:—arranging input images in blocks to produce input image blocks,—subjecting the input image blocks to block processing including: transform into a transformed domain, subjecting the image blocks transformed into a transformed domain to filtering, subjecting the image blocks transformed into a transformed domain and filtered to inverse transform implementing an inverse transform with respect to the previous transform into a transformed domain, thus producing a set of processed blocks. The set of processed blocks, which is recomposeable to an image pyramid, may be used, e.g., in detecting extrema points in images in the pyramid, extracting a patch of given size around the extrema points detected, and processing the patch to obtain local descriptors such as SIFT descriptors of a feature.
Abstract:
Image defects in digital images are easily detectable by the human eye but may be difficult to detect in a computer-implemented fashion. In an embodiment of a digital-image-acquisition device, defects are removed on the CFA domain before color interpolation takes place. In order to allow cancellation of couplets of defective pixels, a two pass embodiment is presented. Such embodiment presents methods and systems that can remove both couplets and singlets without damaging the image. The system includes a ring corrector that detects a defect in the ring of pixels that surround a central pixel, a singlet corrector that detects and corrects the central pixel and removes a couplet if the ring corrector is activated, whereas if the ring corrector is switched off, the singlet corrector only removes singlets, and a peak-and-valley detector that avoids overcorrection by avoiding correcting signal peaks or valleys in case of spikes or drops in signal.
Abstract:
A panning device for processing relative motion vectors and absolute motion vectors obtained from a video sequence, includes: a panning filter module, such as a high-pass IIR filter, for subjecting relative motion vectors to panning processing, an adder module for adding the relative motion vectors subjected to panning in the panning filter module to absolute motion vectors to obtain respective summed values of motion vectors, a clipping module for subjecting the summed values of motion vectors obtained in the adder module to clipping according to a selected cropping window for obtaining final output absolute motion vectors, a first leak integrator arranged after the panning filter module, and a second leak integrator arranged after the clipping module.
Abstract:
A method of processing digital images by transforming a set of pixels from a three-dimensional space to a normalized two-dimensional space, determining a membership class and membership class level of each pixel in the set of pixels, and selectively modifying colors of pixels in the set of pixels based on the determined membership classes and membership class levels.
Abstract:
A sequence of images is processed to generate optical flow data including a list of motion vectors. The motion vectors are grouped based on orientation into a first set of moving away motion vectors and a second set of moving towards motion vectors. A vanishing point is determined as a function of the first set of motion vectors and a center position of the images is determined. Pan and tilt information is computed from the distance difference between the vanishing point and the center position. Approaching objects are identified from the second set as a function of position, length and orientation, thereby identifying overtaking vehicles. Distances to the approaching objects are determined from object position, camera focal length, and pan and tilt information. A warning signal is issued as a function of the distances.
Abstract:
Method for generating a lane departure warning in a vehicle, comprising acquiring a plurality of frames of a digital image of a road on which the vehicle is running, the digital image of a road including the image of a lane within which the vehicle is running and of marking lines of the lane, for each of the acquired frames, extracting edge points of the frame, analyzing the edge points to evaluate a lane departure status, the evaluation including performing a lane departure verification procedure including identifying in the frame points representative of the position of the lane marking lines, generating a lane departure alert if a lane departure status is detected by the lane departure verification procedure. In the described method, the lane departure verification procedure includes comparing the position of the points to reference positions of the lane, the reference positions of the lane being obtained by a lane calibration procedure performed on a set of acquired frames, the lane calibration procedure including filtering edge points of the image frame belonging to an area of a horizontal stripe of the frame including a plurality of rows of the frame.