Abstract: A method for monitoring headway to an object performable in a computerized system including a camera mounted in a moving vehicle. The camera acquires in real time multiple image frames including respectively multiple images of the object within a field of view of the camera. An edge is detected in in the images of the object. A smoothed measurement is performed of a dimension the edge. Range to the object is calculated in real time, based on the smoothed measurement.

Abstract: A system and method that identifies mode of transportation and transportation patterns of users by matching the vehicle location information and other available information to cellular location data.

Abstract: A method for monitoring headway to an object performable in a computerized system including a camera mounted in a moving vehicle. The camera acquires in real time multiple image frames including respectively multiple images of the object within a field of view of the camera. An edge is detected in in the images of the object. A smoothed measurement is performed of a dimension the edge. Range to the object is calculated in real time, based on the smoothed measurement.

Abstract: Systems and methods for image-based self-localization of an image capture device, include receiving a query image of an undetermined location of the image and comparing the query image to a set of geotagged reference images to determine a location of the query image. The system and method may alternatively compare a series of query images to reference images or portions of feature vectors generated from said query images and reference images to determine the closest query image in the series to respective reference images. The set of geotagged reference images may include a sequence of previously obtained reference images of a route, each reference image corresponding to a known geolocation. The geolocation of the user may be determined based on the location of the query image within the set. Ambient conditions of the images may be used to improve comparison of a query image to reference images. Segment and/or abstractions of cell images may be used to reduce computational and/or communications resources.

Abstract: A method for monitoring headway to an object performable in a computerized system including a camera mounted in a moving vehicle. The camera acquires in real time multiple image frames including respectively multiple images of the object within a field of view of the camera. An edge is detected in in the images of the object. A smoothed measurement is performed of a dimension the edge. Range to the object is calculated in real time, based on the smoothed measurement.

Abstract: In order for the feature extractors to operate with sufficient accuracy, a high degree of training is required. In this situation, a neural network implementing the feature extractor may be trained by providing it with images having known correspondence. A 3D model of a city may be utilized in order to train a neural network for location detection. 3D models are sophisticated and allow manipulation of viewer perspective and ambient features such as day/night sky variations, weather variations, and occlusion placement. Various manipulations may be executed in order to generate vast numbers of image pairs having known correspondence despite having variations. These image pairs with known correspondence may be utilized to train the neural network to be able to generate feature maps from query images and identify correspondence between query image feature maps and reference feature maps. This training can be accomplished without requiring the capture of real images with known correspondence.

Abstract: In order for the feature extractors to operate with sufficient accuracy, a high degree of training is required. In this situation, a neural network implementing the feature extractor may be trained by providing it with images having known correspondence. A 3D model of a city may be utilized in order to train a neural network for location detection. 3D models are sophisticated and allow manipulation of viewer perspective and ambient features such as day/night sky variations, weather variations, and occlusion placement. Various manipulations may be executed in order to generate vast numbers of image pairs having known correspondence despite having variations. These image pairs with known correspondence may be utilized to train the neural network to be able to generate feature maps from query images and identify correspondence between query image feature maps and reference feature maps. This training can be accomplished without requiring the capture of real images with known correspondence.

Abstract: A system and method that analyzes root cause of congestion at specific road sections. A system and method that differentiates between travelers using different modes of transportation. A system and method that analyzes root cause of parking overload. A system and method that performs demographic analysis of people travelling at specific road sections. Certain embodiments of the above systems and methods use data derived from cellular networks. Certain embodiments of the above systems and methods teach real time analysis while others teach non real-time analysis.

Abstract: A method for monitoring headway to an object performable in a computerized system including a camera mounted in a moving vehicle. The camera acquires in real time multiple image frames including respectively multiple images of the object within a field of view of the camera. An edge is detected in in the images of the object. A smoothed measurement is performed of a dimension the edge. Range to the object is calculated in real time, based on the smoothed measurement.

Abstract: A method for monitoring headway to an object performable in a computerized system including a camera mounted in a moving vehicle. The camera acquires in real time multiple image frames including respectively multiple images of the object within a field of view of the camera. An edge is detected in in the images of the object. A smoothed measurement is performed of a dimension the edge. Range to the object is calculated in real time, based on the smoothed measurement.

Abstract: A system and method that analyzes root cause of congestion at specific road sections. A system and method that differentiates between travelers using different modes of transportation. A system and method that analyzes root cause of parking overload. A system and method that performs demographic analysis of people travelling at specific road sections. Certain embodiments of the above systems and methods use data derived from cellular networks. Certain embodiments of the above systems and methods teach real time analysis while others teach non real-time analysis.

Abstract: A method for monitoring headway to an object performable in a computerized system including a camera mounted in a moving vehicle. The camera acquires in real time multiple image frames including respectively multiple images of the object within a field of view of the camera. An edge is detected in in the images of the object. A smoothed measurement is performed of a dimension the edge. Range to the object is calculated in real time, based on the smoothed measurement.

Abstract: A method for monitoring headway to an object performable in a computerized system including a camera mounted in a moving vehicle. The camera acquires in real time multiple image frames including respectively multiple images of the object within a field of view of the camera. An edge is detected in the images of the object. A smoothed measurement is performed of a dimension the edge. Range to the object is calculated in real time, based on the smoothed measurement.

Abstract: A method for monitoring headway to an object performable in a computerized system including a camera mounted in a moving vehicle. The camera acquires in real time multiple image frames including respectively multiple images of the object within a field of view of the camera. An edge is detected in the images of the object. A smoothed measurement is performed of a dimension the edge. Range to the object is calculated in real time, based on the smoothed measurement.

Abstract: In a computerized system including a camera mounted in a moving vehicle. The camera acquires consecutively in real time image frames including images of an object within the field of view of the camera. Range to the object from the moving vehicle is determined in real time. A dimension, e.g. a width, is measured in the respective images of two or more image frames, thereby producing measurements of the dimension. The measurements are processed to produce a smoothed measurement of the dimension. The dimension is measured subsequently in one or more subsequent frames. The range from the vehicle to the object is calculated in real time based on the smoothed measurement and the subsequent measurements. The processing preferably includes calculating recursively the smoothed dimension using a Kalman filter.

Abstract: Continuously extracting traffic load and speed on roads within the coverage area of a cellular network using only data that arrives to the cellular switch implanted in the following stages: (a) a learning phase, which can include vehicle(s) with a location device (i.e., a GPS system) traveling across the covered routes and collecting cellular data and location data in parallel, analyzing the accumulated data and processing the date to create a reference database; and (b) an operational stage in which communications on the cellular network are monitored continuously, and matched against the reference database in to locate their route and speed. The data analysis and data base structure are provided in a manner that enables in the operational stage fast and reliable initial identification of the vehicle's route, based only on the cell ID of handovers; follow-up forward and backwards of the vehicle's route; and real-time incident detection.

Abstract: A system and method that detects related events in the cellular comm. network and its derivatives with minimum overhead and in a changing cellular environment, both in the installation stage of a system, as well as during continuous operation.

Abstract: In a computerized system including a camera mounted in a moving vehicle. The camera acquires consecutively in real time image frames including images of an object within the field of view of the camera. Range to the object from the moving vehicle is determined in real time. A dimension, e.g. a width, is measured in the respective images of two or more image frames, thereby producing measurements of the dimension. The measurements are processed to produce a smoothed measurement of the dimension. The dimension is measured subsequently in one or more subsequent frames. The range from the vehicle to the object is calculated in real time based on the smoothed measurement and the subsequent measurements. The processing preferably includes calculating recursively the smoothed dimension using a Kalman filter.

Abstract: A system and method that continuously extracts traffic load and speed on roads within the coverage area of a cellular network. The data is extracted directly from communications in a cellular network without using any external sensors. The method enables correlating a car to a road it travels on and determining its speed by using only the partial data that arrives to the cellular switch. The method consists of the following stages: A learn phase, which can include a vehicle(s) with a location device (say GPS system) travels across the covered routes within a designated area and collects the cellular data (cell handover sequences and signal strength reports) and location data in parallel. The accumulated data is then analyzed and processed to create the reference database. An operational stage in which communications on the cellular network control channel are monitored continuously, and matched against the reference database in order to locate their route and speed.

Abstract: A system and method that continuously extracts traffic load and speed on roads within the coverage area of a cellular network. The data is extracted directly from the higher level of communications in a cellular network without using any external sensors. The cellular data used by the system includes cell handover sequences as the major input. The method consists of a learn phase in which a vehicle with a location device (say GPS system) travels across the covered routes and collects the cellular data and location data in parallel. In the continuous data collection stage the cellular data is processed and correlated to the data collected in the learn phase to yield the route and exact location of the vehicle on it. Each such two locations yield the travel distance and time, and thus the driving speed in this route section. This procedure is performed continuously across the covered area to yield the traffic load and speed.