Abstract: A method for calculation of firearm sight calibration instructions by processing an image of a shooting target. The method comprises receiving at least one image from at least one imaging device, the at least one image depicts a shooting target with a shot group comprising a plurality of bullet holes, receiving an indication of a firearm type and/or a firearm sight type to calibrate, using at least one hardware processor for calculating firearm sight calibration instructions according to at least one relative location of one of the plurality of bullet holes in relation to another of the plurality of bullet holes by processing the at least one image and at least one predefined parameter of the firearm and/or the firearm sight type, and outputting presentation instructions to present the firearm sight calibration instructions on a display of a client device.

Abstract: A method for calculation of firearm sight calibration instructions by processing an image of a shooting target. The method comprises receiving at least one image from at least one imaging device, the at least one image depicts a shooting target with a shot group comprising a plurality of bullet holes, receiving an indication of a firearm type and/or a firearm sight type to calibrate, using at least one hardware processor for calculating firearm sight calibration instructions according to at least one relative location of one of the plurality of bullet holes in relation to another of the plurality of bullet holes by processing the at least one image and at least one predefined parameter of the firearm and/or the firearm sight type, and outputting presentation instructions to present the firearm sight calibration instructions on a display of a client device.

Abstract: A method for calculation of firearm sight calibration instructions by processing an image of a shooting target. The method comprises receiving at least one image from at least one imaging device, the at least one image depicts a shooting target with a shot group comprising a plurality of bullet holes, receiving an indication of a firearm type and/or a firearm sight type to calibrate, using at least one hardware processor for calculating firearm sight calibration instructions according to at least one relative location of one of the plurality of bullet holes in relation to another of the plurality of bullet holes by processing the at least one image and at least one predefined parameter of the firearm and/or the firearm sight type, and outputting presentation instructions to present the firearm sight calibration instructions on a display of a client device.

Abstract: A method for calculation of firearm sight calibration instructions by processing an image of a shooting target. The method comprises receiving at least one image from at least one imaging device, the at least one image depicts a shooting target with a shot group comprising a plurality of bullet holes, receiving an indication of a firearm type and/or a firearm sight type to calibrate, using at least one hardware processor for calculating firearm sight calibration instructions according to at least one relative location of one of the plurality of bullet holes in relation to another of the plurality of bullet holes by processing the at least one image and at least one predefined parameter of the firearm and/or the firearm sight type, and outputting presentation instructions to present the firearm sight calibration instructions on a display of a client device.

Abstract: The invention relates to a method of predicting personality characteristic from images of a subject person's face, comprising: a) collecting training images of multiple persons for training propose, the images associated with metadata characteristics of human personality; b) grouping the collected training images into training groups; c) training at least one image-based classifier to predict at least one characteristics of human personality from at least one image of a second person; and d) applying the at least one image-based classifier to at least one image of the subject person for outputting a prediction of at least one human personality characteristic of the subject person.

Abstract: The invention relates to a method of predicting personality characteristic from images of a subject person's face, comprising: a) collecting training images of multiple persons for training propose, the images associated with metadata characteristics of human personality; b) grouping the collected training images into training groups; c) training at least one image-based classifier to predict at least one characteristics of human personality from at least one image of a second person; and d) applying the at least one image-based classifier to at least one image of the subject person for outputting a prediction of at least one human personality characteristic of the subject person.

Abstract: A method for deriving accurate body size measures of a user from a sequence of 2D images includes: a) automatically guiding the user through a sequence of body poses and motions; b) scanning the body of said user by obtaining a sequence of raw 2D images of said user as captured by at least one camera during said guided sequence of poses and motions; c) analyzing the behavior of said user to ensure that the user follows the provided instructions; d) extracting and encoding 2D shape data descriptors from said sequence of images by using a 2D shape analyzer (2DSA); and e) integrating said 2D shape descriptors and data representing the user's position, pose and rotation into a 3D shape model.

Abstract: The present invention relates to a method of predicting personality characteristic from at least one image of a subject person, in particular images of the person's face, comprising: a) collecting training images of multiple persons for training propose, wherein each of said training images is associated with metadata characteristics of human personality; b) grouping said collected training images into training groups according to said associated metadata, either according to same metadata or similar metadata; c) training at least one image-based classifier to predict at least one characteristics of human personality from at least one image of a second person; and d) applying said at least one image-based classifier to at least one image of said subject person for outputting a prediction of at least one human personality characteristic of said subject person.

Abstract: A method for deriving accurate body size measures of a user from a sequence of 2D images includes: a) automatically guiding the user through a sequence of body poses and motions; b) scanning the body of said user by obtaining a sequence of raw 2D images of said user as captured by at least one camera during said guided sequence of poses and motions; c) analyzing the behavior of said user to ensure that the user follows the provided instructions; d) extracting and encoding 2D shape data descriptors from said sequence of images by using a 2D shape analyzer (2DSA); and e) integrating said 2D shape descriptors and data representing the user's position, pose and rotation into a 3D shape model.

Abstract: Generating 3D representations of a scene represented by a first video stream captured by video cameras. Identifying a transition between cameras, retrieving parameters of a first set of viewing configurations, providing 3D video representations representing the scene at several sets of viewing configurations different from the first set of viewing configurations, and generating an integrated video stream enabling 3D display of the scene by integration of at least two video streams having respective sets of viewing configurations, which are mutually different. Another provided process is for synthesizing an image of an object from a first image, captured by a certain camera at a first viewing configuration. Assigning a 3D model to a portion of a segmented object, calculating a modified image of the portion of the object from a viewing configuration different from the first viewing configuration, and embedding the modified image in a frame for stereoscopy.

Abstract: It is provided a method for generating a 3D representation of a scene, initially represented by a first video stream captured by a certain camera at a first set of viewing configurations. The method includes providing video streams compatible with capturing the scene by cameras, and generating an integrated video stream enabling three-dimensional display of the scene by integration of two video streams. The method includes calculating parameters characterizing a viewing configuration by analysis of elements having known geometrical parameters. The scene may be a sport scene which a playing field, a group of on-field objects and a group of background objects. The method includes segmenting a frame to those portions, separately associating each portion to the different viewing configuration, and merging them into a single frame.

Abstract: A method for selecting at least one message from a playlist including a plurality of messages to be played by a message playing device to an exposed audience, each message directed to a target audience. The method comprises choosing a utility function, depending on one or more audience parameters, for each of the messages, periodically measuring the audience parameters pertaining to the exposed audience, calculating utility for each of the messages using the utility function, based on the audience parameters as periodically measured, and selecting a message to play from the playlist based on a cumulative gain attributed to each message from the playlist that has played, wherein the gain is updated with respect to the calculated utility for that message. Other methods and systems are also disclosed and claimed.

Abstract: A method of selecting key-frames (230) from a video sequence (210, 215) by comparing each frame in the video sequence with respect to its preceding and subsequent key-frames for redundancy where the comparison involves region and motion analysis. The video sequence is optionally pre-processed to detect graphic overlay. The key-frame set is optionally post-processed (250) to optimize the resulting set for face or other object recognition.

Abstract: A method for generating an index of the text of a video image sequence is provided. The method includes the steps of determining the image text objects in each of a plurality of frames of the video image sequence; comparing the image text objects in each of the plurality of frames of the video image sequence to obtain a record of frame sequences having matching image text objects; extracting the content for each of the similar image text objects in text string format; and storing the text string for each image text object as a video text object in a retrievable medium.

Abstract: Apparatus for automatic electronic replacement of a billboard in a video image including an automatic camera orientation measurement apparatus including motion measurement means operative to measure the Field of View (FOV) of the TV camera relative to a known reference position.

Abstract: A method for selecting a channel of interest from a plurality of communication channels which carry audio or video information, by: extracting image or sound characteristic data from said audio or video information, searching for specific content of interest based on said image or sound characteristic data and selecting a channel based on said content of interest is described. Image and sound characteristic data are stored on a content-based channel search server, which includes video search engines capable of matching attributes related to user interest profiles with data corresponding to current content of multiple channels. User interact with the server via client terminals, which communicate with the server using the Internet protocol. Client terminal receive search results corresponding to matches between channel content and user profile. The client terminal controls a variety of viewing, recording and logging devices.

Abstract: A method of determining the position of a TV camera relative to a patterned panel being viewed by the TV camera including the steps of:

Abstract: A method of determining the position of a TV camera relative to a patterned panel being viewed by the TV camera including the steps of: identifying a plurality of edge points of the pattern from the video signal produced by said camera and using these edge points to calculate the perspective of the pattern relative to the camera.

Abstract: Apparatus for automatic replacement of a billboard in a video image is provided. The billboard comprises a chroma-key surface, and the apparatus includes a video camera for viewing the billboard, and a chroma-key unit operative to detect at least one chroma-key color of the billboard chroma-key surface. A reference color of the chroma-key unit is adjustable to conform to the color of the chrom-key surface, thereby enabling the chroma-key unit to correctly identify the billboard surface and to correctly replace the chroma-key surface of the billboard by a virtual advertisement in a video image with correct occlusion of any foreground object.

Abstract: Apparatus for automatic electronic replacement of a billboard in a video image including an automatic camera orientation measurement apparatus including motion measurement means operative to measure the Field of View (FOV) of the TV camera relative to a known reference position.