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: 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: 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: 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: 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: In an embodiment, focusing an image-capture device such as, e.g., a camera including an optical system displaceable in opposite directions (A, B) via a focusing actuator, is controlled by evaluating a scale factor for the images acquired by the device. An accumulated value of the variations of the scale factor over a time interval (e.g., over a number of frames) is produced and the absolute value thereof is compared against a threshold. If the threshold is reached, which may be indicative of a zoom movement resulting in image de-focusing, a refocusing action is activated by displacing the optical system via the focusing actuator in the one or the other of the opposite focusing directions (A or B) as a function of whether the accumulated value exhibits an increase or a decrease (i.e., whether the accumulated value is positive or negative).

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: In an embodiment, focusing an image-capture device such as, e.g., a camera including an optical system displaceable in opposite directions (A, B) via a focusing actuator, is controlled by evaluating a scale factor for the images acquired by the device. An accumulated value of the variations of the scale factor over a time interval (e.g., over a number of frames) is produced and the absolute value thereof is compared against a threshold. If the threshold is reached, which may be indicative of a zoom movement resulting in image de-focusing, a refocusing action is activated by displacing the optical system via the focusing actuator in the one or the other of the opposite focusing directions (A or B) as a function of whether the accumulated value exhibits an increase or a decrease (i.e., whether the accumulated value is positive or negative).

Abstract: A method for associating with a digital image a class of a plurality of predefined classes having respective models, the method including the phases of dividing the digital image pixel by pixel into one or more regions belonging to a set of predefined regions that differ from each other on account of their type of content, the division being effected by establishing whether or not a pixel of the image belongs to a respective region on the basis of an operation of analyzing the parameters this pixel, the analysis operation being carried out by verifying that the parameters satisfy predefined conditions and/or logico-mathematical relationships of belonging to the respective region, acquiring from the digital image divided into regions information regarding the regions that are present in it, comparing this information with at least one model characterizing a respective class of said plurality, and associating with the digital image a class on the basis of the comparison phase.

Abstract: A method of obtaining a depth map from a single digital image of a three-dimensional scene containing geometric objects is provided that includes the identification in the image of at least one horizontal plane or one vertical plane of the three-dimensional scene and the assignment to every point of the image forming part of the identified plane, or to each one of the identified planes, of a depth level according to its distance from, respectively, a predetermined horizontal or vertical reference straight line of the image. In particular, the identification of at least one plane includes the identification in the image of at least two vanishing lines corresponding to two parallel lines in the plane and the assignment of a depth level made in accordance with the angular coefficients of the identified vanishing lines. Also included is a completely automatic method for obtaining a depth map from a single digital image of any three-dimensional scene.

Abstract: A method for associating with a digital image a class of a plurality of predefined classes having respective models, the method including the phases of dividing the digital image pixel by pixel into one or more regions belonging to a set of predefined regions that differ from each other on account of their type of content, the division being effected by establishing whether or not a pixel of the image belongs to a respective region on the basis of an operation of analyzing the parameters this pixel, the analysis operation being carried out by verifying that the parameters satisfy predefined conditions and/or logico-mathematical relationships of belonging to the respective region, acquiring from the digital image divided into regions information regarding the regions that are present in it, comparing this information with at least one model characterizing a respective class of said plurality, and associating with the digital image a class on the basis of the comparison phase.

Abstract: A method for associating with a digital image a class of a plurality of predefined classes having respective models, the method including the phases of dividing the digital image pixel by pixel into one or more regions belonging to a set of predefined regions that differ from each other on account of their type of content, the division being effected by establishing whether or not a pixel of the image belongs to a respective region on the basis of an operation of analyzing the parameters this pixel, the analysis operation being carried out by verifying that the parameters satisfy predefined conditions and/or logico-mathematical relationships of belonging to the respective region, acquiring from the digital image divided into regions information regarding the regions that are present in it, comparing this information with at least one model characterizing a respective class of said plurality, and associating with the digital image a class on the basis of the comparison phase.

Abstract: A method of obtaining a depth map from a single digital image of a three-dimensional scene containing geometric objects is provided that includes the identification in the image of at least one horizontal plane or one vertical plane of the three-dimensional scene and the assignment to every point of the image forming part of the identified plane, or to each one of the identified planes, of a depth level according to its distance from, respectively, a predetermined horizontal or vertical reference straight line of the image. In particular, the identification of at least one plane includes the identification in the image of at least two vanishing lines corresponding to two parallel lines in the plane and the assignment of a depth level made in accordance with the angular coefficients of the identified vanishing lines. Also included is a completely automatic method for obtaining a depth map from a single digital image of any three-dimensional scene.