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 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:
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:
A security system can conditionally grant or deny access to a protected area using an artificial intelligence system to analyze images. In an example, an access control method can include receiving candidate information about a face and gesture from a first individual and receiving other image information from or about a second individual. The candidate information can be analyzed using a neural network-based recognition processor that can provide a first recognition result indicating whether the first individual corresponds to a first enrollee of the security system, and can provide a second recognition result indicating whether the second individual corresponds to a second enrollee of the security system. The example method can include receiving a passcode, such as from the first individual. Access can be conditionally granted or denied based on the passcode and the recognition results.
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:
A security system can conditionally grant or deny access to a protected area using an artificial intelligence system to analyze images. In an example, an access control method can include receiving candidate information about a face and gesture from a first individual and receiving other image information from or about a second individual. The candidate information can be analyzed using a neural network-based recognition processor that can provide a first recognition result indicating whether the first individual corresponds to a first enrollee of the security system, and can provide a second recognition result indicating whether the second individual corresponds to a second enrollee of the security system. The example method can include receiving a passcode, such as from the first individual. Access can be conditionally granted or denied based on the passcode and the recognition results.
Abstract:
Systems can be configured for detecting license plates and recognizing characters in license plates. In an example, a system can receive an image and identify one or more regions in the image that include a license plate. Character recognition can be performed in the one or more regions to determine contents of a candidate license plate. Location-specific information about a license plate format can be used together with the determined contents of the candidate license plate to determine if the recognized characters are valid.
Abstract:
A security system can conditionally grant or deny access to a protected area using an artificial intelligence system to analyze images. In an example, an access control method can include receiving candidate information about a face and gesture from a first individual and receiving other image information from or about a second individual. The candidate information can be analyzed using a neural network-based recognition processor that can provide a first recognition result indicating whether the first individual corresponds to a first enrollee of the security system, and can provide a second recognition result indicating whether the second individual corresponds to a second enrollee of the security system. The example method can include receiving a passcode, such as from the first individual. Access can be conditionally granted or denied based on the passcode and the recognition results.
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 to a client device; and facilitate at least any one of a user defined playback of the single stream of the recognized event, user defined monitoring of the audio-video sequence preceding and, or succeeding the recognized event, and, or remote provisioning of the processor-controlled video camera, whereby the playback and, or provisioning is facilitated via a client device user interface.
Abstract:
Person or object authentication can be performed using artificial intelligence-enabled systems. Reference information, such as for use in comparisons or assessments for authentication, can be updated over time to accommodate changes in an individual's appearance, voice, or behavior. In an example, reference information can be updated automatically with test data, or reference information can be updated conditionally, based on instructions from a system administrator. Various types of media can be used for authentication, including image information, audio information, or biometric information. In an example, authentication can be performed wholly or partially at an edge device such as a security panel in an installed security system.