Abstract: The invention is based, in part, on a system and method designed to be able to easily and automatically scale up to millions of cameras and users. To do this, this discourse teaches use of modern cloud computing technology, including automated service provisioning, automated virtual machine migration services, RESTful API, and various firewall traversing methods to facilitate the scaling process. Moreover, the system and method described herein teaches scalable cloud solutions providing for higher though-put camera provisioning and event recognition. The network may segregate the retrieval server from the storage server, and by doing so, minimizing the load on any one server and improving network efficiency and scalability.

Abstract: The present invention discloses methods and systems face recognition. Face recognition involves receiving an image/frame, detecting one or more faces in the image, detecting feature points for each of the detected faces in the image, aligning and normalizing the detected feature points, extracting feature descriptors based on the detected feature points and matching the extracted feature descriptors with a set of pre-stored images for face recognition.

Abstract: The present invention discloses methods, systems and computer programmable products for detecting license plates and recognizing characters in the license plates. The system receives an image and identifies one or more regions including a license plate. The one or more regions are converted into a plurality of binarized images, which are then filtered to remove noise. Next, one or more clusters of characters are identified in the plurality of binarized images. The one or more clusters of characters are analyzed to recognize a set of characters, wherein each character in the set includes a confidence value.

Abstract: Method of tracking moveable objects (typically tagged objects that are moved by actors e.g. people, vehicles) by combining and analyzing data obtained from multiple types of sensors, such as video cameras, RFID tag readers, GPS sensors, and WiFi transceivers. Objects may be tagged by RFID tags, NFC tags, bar codes, or even tagged by visual appearance. The system operates in near real-time, and compensates for errors in sensor readings and missing sensor data by modeling object and actor movement according to a plurality of possible paths, weighting data from some sensors higher than others according to estimates of sensor accuracy, and weighing the probability of certain paths according to various other rules and penalty cost parameters. The system can maintain a comprehensive database which can be queried as to which actors associate with which objects, and vice versa. Other data pertaining to object location and association can also be obtained.

Abstract: The present invention discloses methods, systems, and computer programmable products for tracking objects across a first frame and a second frame of a video. An object tracking system computes a cost function between each object in the first frame and each object in the second frame. Further, a pair of objects is selected from the first frame and the second frame based on a pre-defined criteria which is based on the computed cost function. Thereafter, the object tracking system established a correspondence between the selected pair of objects.

Abstract: The present invention discloses methods and systems face recognition. Face recognition involves receiving an image/frame, detecting one or more faces in the image, detecting feature points for each of the detected faces in the image, aligning and normalizing the detected feature points, extracting feature descriptors based on the detected feature points and matching the extracted feature descriptors with a set of pre-stored images for face recognition.

Abstract: The present invention discloses methods and systems for recognizing an object in an input image based on stored training images. An object recognition system the input image, computes a signature of the input image, compares the signature with one or more stored signatures and retrieves one or more matching images from the set of training images. The matching images are then displayed to the user for further action.

Abstract: The invention is based, in part, on a system for allowing at least one client to real-time monitor and, or playback at least one real-world recognized event via at least one processor-controlled video camera, said system comprising: a processor; a non-transitory storage medium coupled to the processor; encoded instructions stored in the non-transitory storage medium, which when executed by the processor, cause the processor to: detect a threshold-grade event from audio-video data of a real-world environment captured from a processor-controlled video camera by an event detection module within an event management system applying event detection parameters; analyze the threshold-grade event for categorization into any one of a recognized event by an event recognition module within the event management system applying event recognition parameters; transmit at least any one of a single stream of the recognized event and, or a single stream of a audio-video sequence succeeding and, or preceding the recognized event

Abstract: Method of tracking moveable objects (typically tagged objects that are moved by actors e.g. people, vehicles) by combining and analyzing data obtained from multiple types of sensors, such as video cameras, RFID tag readers, GPS sensors, and WiFi transceivers. Objects may be tagged by RFID tags, NFC tags, bar codes, or even tagged by visual appearance. The system operates in near real-time, and compensates for errors in sensor readings and missing sensor data by modeling object and actor movement according to a plurality of possible paths, weighting data from some sensors higher than others according to estimates of sensor accuracy, and weighing the probability of certain paths according to various other rules and penalty cost parameters. The system can maintain a comprehensive database which can be queried as to which actors associate with which objects, and vice versa. Other data pertaining to object location and association can also be obtained.