Abstract: A platform, device and process for capturing images of the surface of a gaming table and determining the quantity, identity, and arrangement of chips bet at a gaming table. Image data is captured corresponding to the one or more chips positioned in at least one betting area on a gaming surface of the respective gaming table and the data is processed to filter out the background, establish a two dimensional grid of points of interests and corresponding histograms for classifying the one or more chips through identifying a dominant classification of each row in the grid of points of interests.

Abstract: A platform, device and process for capturing images of the surface of a gaming table and determining the quantity, identity, and arrangement of chips bet at a gaming table. Image data is captured corresponding to the one or more chips positioned in at least one betting area on a gaming surface of the respective gaming table and the data is processed to filter out the background, establish a two dimensional grid of points of interests and corresponding histograms for classifying the one or more chips through identifying a dominant classification of each row in the grid of points of interests.

Abstract: Systems, methods, devices, and computer readable media for monitoring card game activities at gaming tables, such as for example, counting the number of card hands at gaming tables. The devices may include a sensor array network to detect game events; a microcontroller for running logic level code for checking sensors of the sensors of the sensor array network for pre-defined thresholds defining the detected game events and in response generating game event data; and a connection cable for coupling to a server device for transmitting the game event data. Systems may connect client hardware devices with sensors for monitoring card game activities. A game monitoring server may collect, process and aggregate hand event data received from the client hardware devices to generate hand count data for gaming tables. A front end interface device may receive notifications relating to hand count data for provision to end user systems.

Abstract: System, processes and devices for monitoring betting activities using bet recognition devices and a server. Each bet recognition device has an imaging component for capturing image data for a gaming table surface. The bet recognition device receives calibration data for calibrating the bet recognition device. A server processor coupled to a data store processes the image data received from the bet recognition devices over the network to detect, for each betting area, a number of chips and a final bet value for the chips.

Abstract: System, processes and devices for monitoring betting activities using bet recognition devices and a server. Each bet recognition device has an imaging component for capturing image data for a gaming table surface. The bet recognition device receives calibration data for calibrating the bet recognition device. A server processor coupled to a data store processes the image data received from the bet recognition devices over the network to detect, for each betting area, a number of chips and a final bet value for the chips.

Abstract: Embodiments described herein relate to systems and methods for monitoring progressive game activities at a plurality of gaming tables. For example, embodiments described herein relate to systems and methods for monitoring that a bet for playing a progressive game was made, the amount of the bet, the position of the bet, the identification of the player who made the bet and the identification of the gaming table at which the bet was made. A progressive jackpot metric may be computed based on the data captured at the gaming table for increasing or decreasing one or more progressive jackpots. Visual elements corresponding to the one or more progressive jackpots may be rendered on a jackpot interface display.

Abstract: A platform, device and process for capturing images of the surface of a gaming table and determining the quantity, identity, and arrangement of chips bet at a gaming table. Image data is captured corresponding to the one or more chips positioned in at least one betting area on a gaming surface of the respective gaming table and the data is processed to filter out the background, establish a two dimensional grid of points of interests and corresponding histograms for classifying the one or more chips through identifying a dominant classification of each row in the grid of points of interests.

Abstract: System, processes and devices for monitoring betting activities using bet recognition devices and a server. Each bet recognition device has an imaging component for capturing image data for a gaming table surface. The bet recognition device receives calibration data for calibrating the bet recognition device. A server processor coupled to a data store processes the image data received from the bet recognition devices over the network to detect, for each betting area, a number of chips and a final bet value for the chips.

Abstract: A platform, device and process for capturing images of the surface of a gaming table and determining the quantity, identity, and arrangement of chips bet at a gaming table. Image data is captured corresponding to the one or more chips positioned in at least one betting area on a gaming surface of the respective gaming table and the data is processed to filter out the background, establish a two dimensional grid of points of interests and corresponding histograms for classifying the one or more chips through identifying a dominant classification of each row in the grid of points of interests.

Abstract: System, processes and devices for monitoring betting activities using bet recognition devices and a server. Each bet recognition device has an imaging component for capturing image data for a gaming table surface. The bet recognition device receives calibration data for calibrating the bet recognition device. A server processor coupled to a data store processes the image data received from the bet recognition devices over the network to detect, for each betting area, a number of chips and a final bet value for the chips.

Abstract: Systems, methods, devices, and computer readable media for monitoring card game activities at gaming tables, such as for example, counting the number of card hands at gaming tables. The devices may include a sensor array network to detect game events; a microcontroller for running logic level code for checking sensors of the sensors of the sensor array network for pre-defined thresholds defining the detected game events and in response generating game event data; and a connection cable for coupling to a server device for transmitting the game event data. Systems may connect client hardware devices with sensors for monitoring card game activities. A game monitoring server may collect, process and aggregate hand event data received from the client hardware devices to generate hand count data for gaming tables. A front end interface device may receive notifications relating to hand count data for provision to end user systems.

Abstract: Systems, methods, devices, and computer readable media for monitoring card game activities at gaming tables, such as for example, counting the number of card hands at gaming tables. The devices may include a sensor array network to detect game events; a microcontroller for running logic level code for checking sensors of the sensors of the sensor array network for pre-defined thresholds defining the detected game events and in response generating game event data; and a connection cable for coupling to a server device for transmitting the game event data. Systems may connect client hardware devices with sensors for monitoring card game activities. A game monitoring server may collect, process and aggregate hand event data received from the client hardware devices to generate hand count data for gaming tables. A front end interface device may receive notifications relating to hand count data for provision to end user systems.

Abstract: System, processes and devices for monitoring betting activities using bet recognition devices and a server. Each bet recognition device has an imaging component for capturing image data for a gaming table surface. The bet recognition device receives calibration data for calibrating the bet recognition device. A server processor coupled to a data store processes the image data received from the bet recognition devices over the network to detect, for each betting area, a number of chips and a final bet value for the chips.

Abstract: System, processes and devices for monitoring betting activities using bet recognition devices and a server. Each bet recognition device has an imaging component for capturing image data for a gaming table surface. The bet recognition device receives calibration data for calibrating the bet recognition device. A server processor coupled to a data store processes the image data received from the bet recognition devices over the network to detect, for each betting area, a number of chips and a final bet value for the chips.

Abstract: A platform, device and process for capturing images of the surface of a gaming table and determining the quantity, identity, and arrangement of chips bet at a gaming table. Image data is captured corresponding to the one or more chips positioned in at least one betting area on a gaming surface of the respective gaming table and the data is processed to filter out the background, establish a two dimensional grid of points of interests and corresponding histograms for classifying the one or more chips through identifying a dominant classification of each row in the grid of points of interests.

Abstract: Systems, methods, devices, and computer readable media for monitoring card game activities at gaming tables, such as for example, counting the number of card hands at gaming tables. The devices may include a sensor array network to detect game events; a microcontroller for running logic level code for checking sensors of the sensors of the sensor array network for pre-defined thresholds defining the detected game events and in response generating game event data; and a connection cable for coupling to a server device for transmitting the game event data. Systems may connect client hardware devices with sensors for monitoring card game activities. A game monitoring server may collect, process and aggregate hand event data received from the client hardware devices to generate hand count data for gaming tables. A front end interface device may receive notifications relating to hand count data for provision to end user systems.

Abstract: Systems and method described herein present techniques for identifying a gesture using gesture data compressed by principal joint variable analysis. A classifier of a gesture recognition system may receive a frame comprising a set of gesture data points identifying locations of body parts of a subject. The classifier may determining that a subset of the set of gesture data points is sufficient to recognize a first gesture. The subset may be stored into a database in reference to the first gesture. A recognizer may receive a new frame of new gesture data points identifying locations of body parts of a new subject. The recognizer may recognize that the gesture of the new subject corresponds to the first gesture responsive to comparing at least one new gesture data point from the new frame to at least one gesture data point of the subset.

Abstract: System, processes and devices for monitoring betting activities using bet recognition devices and a server. Each bet recognition device has an imaging component for capturing image data for a gaming table surface. The bet recognition device receives calibration data for calibrating the bet recognition device. A server processor coupled to a data store processes the image data received from the bet recognition devices over the network to detect, for each betting area, a number of chips and a final bet value for the chips.

Abstract: The disclosure describes systems and methods of detecting body movements using gesture data. The gesture data may be self-referenced and may be comprised by frames which may identify locations or positions of body parts of a subject with respect to a particular reference point within the frame. A classifier may process frames to learn body movements and store the frames of gesture data in a database. Data comprising frames of self-referenced gesture data may be received by a recognizer which recognizes movements of the subject identified by the frames by matching gesture data of the incoming frames to the classified self-referenced gesture data stored in the database.

Abstract: Systems and method described herein present techniques for identifying a gesture using gesture data compressed by principal joint variable analysis. A classifier of a gesture recognition system may receive a frame comprising a set of gesture data points identifying locations of body parts of a subject. The classifier may determining that a subset of the set of gesture data points is sufficient to recognize a first gesture. The subset may be stored into a database in reference to the first gesture. A recognizer may receive a new frame of new gesture data points identifying locations of body parts of a new subject. The recognizer may recognize that the gesture of the new subject corresponds to the first gesture responsive to comparing at least one new gesture data point from the new frame to at least one gesture data point of the subset.