Polaris Wireless, Inc.

Metawave Communications Corporation

Kathrein-werke Kg

Metawave Communication Corporation

Martin J Feuerstein

David Stevenson Spain, Jr

Tarun Kumar Bhattacharya

Scot Douglas Gordon

Douglas O Reudink

Mark D Reudink

Mahesh B Patel

Manlio Allegra

Jun Liu

Gary Allen Martek

Scot D Gordon

Sheila Reynolds

Yingjie Li

Ji-Hae Yea

Sheldon Kent Meredith

Robert Lewis Martin

Ankit Bansal

Robert Morris Dressler

J Todd Elson

Donglin Shen

Joel Schlekewey

Thomas R Crawford

Data from a wireless network location system is used in conjunction with the known geographic location of a video surveillance area such that the system according to the present invention infers that a person who appears in an image in the video is the user of a mobile phone estimated to be at the person's location. When facial recognition is applied and the person's identity is thus recognized, an association is generated as between the identity according to the facial recognition and the identity of the co-located mobile phone. This association can be critical when there is no personal identification available for a mobile phone such as a pre-paid mobile.

Surveillance system

A method and apparatus are disclosed for estimating whether or not a wireless terminal is in a geographic zone. The illustrative embodiment employs a pattern classifier that is trained on traits of electromagnetic signals at various locations. A computer-executable program is then generated based on the trained pattern classifier, and the program is installed and executed on a subscribed identity module of the terminal.

Estimating whether or not a wireless terminal is in a geographic zone using pattern classification

An apparatus and method are disclosed for tracking a large number of wireless terminals and for estimating the location of the terminals at each instant. Some embodiments of the present invention use a wide variety of factors to determine the order and frequency with which each wireless terminal is located. These factors include, but are not limited to, the history of the location of the wireless terminal, the time of day, and the weather.

Tracking large numbers of wireless terminals

A technique for estimating the location of a wireless terminal at an unknown location in a geographic region is disclosed. The technique is based on the recognition that there are traits of electromagnetic signals that are dependent on topography, the receiver, the location of the transmitter, and other factors. For example, if a particular radio station is known to be received strongly at a first location and weakly at a second location, and a given wireless terminal at an unknown location is receiving the radio station weakly, it is more likely that the wireless terminal is at the second location than at the first location.

Estimating the location of a wireless terminal based on signal path impairment

A method for estimating whether or not a wireless terminal is in a zone is described. The method is based on the following observation: when a wireless terminal is at a particular location, the values of the traits of the ambient electromagnetic signals that vary with location represent a 'fingerprint' or 'signature' for that location. This enables the location of a wireless terminal to be estimated by comparing the observed values of the traits of the ambient electromagnetic signals with the fingerprint for each potential location for the wireless terminal.

Estimating whether or not a wireless terminal is in a zone using radio navigation

An integrated wireless location and facial/speaker-recognition system that provides distinct advantages over facial-recognition systems and speaker-recognition systems of the prior art is disclosed. The integrated system is capable of using information from a wireless location system to improve the performance of the facial recognition and speaker recognition. The system is capable of processing photographs and/or audio samples captured by a camera/microphone at a fixed location (e.g., a digital pan-zoom-tilt (PZT) surveillance camera, etc.) as well as those captured by a mobile camera/microphone (e.g., a digital camera and microphone in a smartphone, etc.). The system also features a feedback mechanism by which the location-informed results can be used to improve the system's recognition abilities.

Wireless location and facial/speaker recognition system

A process and machine for estimating the location of a wireless terminal is disclosed. The illustrative embodiment of the present invention is based on the observation that the signal strength of a signal from a transmitter is different at some locations, and, therefore, the location of a wireless terminal can be estimated by comparing the signal strength it currently observes against a map or database that correlates locations to signal strengths. In accordance with a first example, if a particular radio station is known to be received well at a first location and poorly at a second location, and a given wireless terminal at an unknown location is receiving the radio station poorly, it is more likely that the wireless terminal is at the second location than it is at the first location.

Estimating the location of a wireless terminal based on calibrated signal-strength measurements

Estimating the location of a wireless terminal based on the traits of the multipath components of a signal

Estimating the location of a wireless terminal based on non-uniform locations

Growing community of inventors

Redmond, WA, United States of America

Martin J Feuerstein