Abstract: Image analysis techniques, including object recognition analysis, are applied to images obtained by one or more image capture devices deployed within inventory environments. The object recognition analysis provides object recognition data (that may include one or more recognized product instances) based on stored product (training) images. In turn, a variety of functionalities may be enabled based on the object recognition data. For example, a planogram may be extracted and compared to a target planogram, or at least one product display parameter for a product can be determined and used to assess presence of the product within the inventory environment, or to determine compliance of display of the product with a promotional objective. In yet another embodiment, comparisons may be made within a single image or between multiple images over time to detect potential conditions requiring response. In this manner, efficiency and effectiveness of many previously manually-implemented tasks may be improved.

Abstract: Image analysis techniques, including object recognition analysis, are applied to images obtained by one or more image capture devices deployed within inventory environments. The object recognition analysis provides object recognition data (that may include one or more recognized product instances) based on stored product (training) images. In turn, a variety of functionalities may be enabled based on the object recognition data. For example, a planogram may be extracted and compared to a target planogram, or at least one product display parameter for a product can be determined and used to assess presence of the product within the inventory environment, or to determine compliance of display of the product with a promotional objective. In yet another embodiment, comparisons may be made within a single image or between multiple images over time to detect potential conditions requiring response. In this manner, efficiency and effectiveness of many previously manually-implemented tasks may be improved.

Abstract: Techniques for intelligent and automatic control of sensors for capturing data associated with real time events. Preferably, the sensors are associated with a multimedia database system. For example, a technique for controlling one or more sensors used to capture data associated with an event comprises the following steps/operations. First, sensor data captured in accordance with the event is processed. Then, the one or more sensors are automatically controlled based on information pertaining to the continual activity of at least one of one or more objects and one or more persons associated with the event in real time obtained using at least a portion of the processed data captured in accordance with the event.

Abstract: A method for implementing a closed-loop business process management lifecycle. The method comprising producing at least one to-be process model during a process analysis phase. Storing a copy of the at least one to-be process model. Automating the at least one to-be process model during a process automation phase. Producing data logs by applications implementing the automated to-be process models. Data mining the produced data logs during a process monitoring phase, to produce emerging to-be process models and updated to-be process models of automated to-be process models. Storing the emerging to-be process models and the updated to-be process models; and selecting ones of the stored emerging and updated to-be process models to provide to a new process analysis phase.

Abstract: Image analysis techniques, including object recognition analysis, are applied to images obtained by one or more image capture devices deployed within inventory environments. The object recognition analysis provides object recognition data (that may include one or more recognized product instances) based on stored product (training) images. In turn, a variety of functionalities may be enabled based on the object recognition data. For example, a planogram may be extracted and compared to a target planogram, or at least one product display parameter for a product can be determined and used to assess presence of the product within the inventory environment, or to determine compliance of display of the product with a promotional objective. In yet another embodiment, comparisons may be made within a single image or between multiple images over time to detect potential conditions requiring response. In this manner, efficiency and effectiveness of many previously manually-implemented tasks may be improved.

Abstract: A method for implementing a closed-loop business process management lifecycle. The method comprising producing at least one to-be process model during a process analysis phase. Storing a copy of the at least one to-be process model. Automating the at least one to-be process model during a process automation phase. Producing data logs by applications implementing the automated to-be process models. Data mining the produced data logs during a process monitoring phase, to produce emerging to-be process models and updated to-be process models of automated to-be process models. Storing the emerging to-be process models and the updated to-be process models; and selecting ones of the stored emerging and updated to-be process models to provide to a new process analysis phase.

Abstract: Image analysis techniques, including object recognition analysis, are applied to images obtained by one or more image capture devices deployed within inventory environments. The object recognition analysis provides object recognition data (that may include one or more recognized product instances) based on stored product (training) images. In turn, a variety of functionalities may be enabled based on the object recognition data. For example, a planogram may be extracted and compared to a target planogram, or at least one product display parameter for a product can be determined and used to assess presence of the product within the inventory environment, or to determine compliance of display of the product with a promotional objective. In yet another embodiment, comparisons may be made within a single image or between multiple images over time to detect potential conditions requiring response. In this manner, efficiency and effectiveness of many previously manually-implemented tasks may be improved.

Abstract: Image analysis techniques, including object recognition analysis, are applied to images obtained by one or more image capture devices deployed within inventory environments. The object recognition analysis provides object recognition data (that may include one or more recognized product instances) based on stored product (training) images. In turn, a variety of functionalities may be enabled based on the object recognition data. For example, a planogram may be extracted and compared to a target planogram, or at least one product display parameter for a product can be determined and used to assess presence of the product within the inventory environment, or to determine compliance of display of the product with a promotional objective. In yet another embodiment, comparisons may be made within a single image or between multiple images over time to detect potential conditions requiring response. In this manner, efficiency and effectiveness of many previously manually-implemented tasks may be improved.

Abstract: A performance data mining system combines detailed sensor analysis data with other data sources to discover interesting patterns/rules for performance and utilizes real time sensor analysis to dynamically derive mining results in real time during an event. The system automatically generates advice/strategy and predictions based on specified criteria.

Abstract: Image analysis techniques, including object recognition analysis, are applied to images obtained by one or more image capture devices deployed within inventory environments. The object recognition analysis provides object recognition data (that may include one or more recognized product instances) based on stored product (training) images. In turn, a variety of functionalities may be enabled based on the object recognition data. For example, a planogram may be extracted and compared to a target planogram, or at least one product display parameter for a product can be determined and used to assess presence of the product within the inventory environment, or to determine compliance of display of the product with a promotional objective. In yet another embodiment, comparisons may be made within a single image or between multiple images over time to detect potential conditions requiring response. In this manner, efficiency and effectiveness of many previously manually-implemented tasks may be improved.

Abstract: Image analysis techniques, including object recognition analysis, are applied to images obtained by one or more image capture devices deployed within inventory environments. The object recognition analysis provides object recognition data (that may include one or more recognized product instances) based on stored product (training) images. In turn, a variety of functionalities may be enabled based on the object recognition data. For example, a planogram may be extracted and compared to a target planogram, or at least one product display parameter for a product can be determined and used to assess presence of the product within the inventory environment, or to determine compliance of display of the product with a promotional objective. In yet another embodiment, comparisons may be made within a single image or between multiple images over time to detect potential conditions requiring response. In this manner, efficiency and effectiveness of many previously manually-implemented tasks may be improved.

Abstract: Image analysis techniques, including object recognition analysis, are applied to images obtained by one or more image capture devices deployed within inventory environments. The object recognition analysis provides object recognition data (that may include one or more recognized product instances) based on stored product (training) images. In turn, a variety of functionalities may be enabled based on the object recognition data. For example, a planogram may be extracted and compared to a target planogram, or at least one product display parameter for a product can be determined and used to assess presence of the product within the inventory environment, or to determine compliance of display of the product with a promotional objective. In yet another embodiment, comparisons may be made within a single image or between multiple images over time to detect potential conditions requiring response. In this manner, efficiency and effectiveness of many previously manually-implemented tasks may be improved.

Abstract: Image analysis techniques, including object recognition analysis, are applied to images obtained by one or more image capture devices deployed within inventory environments. The object recognition analysis provides object recognition data (that may include one or more recognized product instances) based on stored product (training) images. In turn, a variety of functionalities may be enabled based on the object recognition data. For example, a planogram may be extracted and compared to a target planogram, or at least one product display parameter for a product can be determined and used to assess presence of the product within the inventory environment, or to determine compliance of display of the product with a promotional objective. In yet another embodiment, comparisons may be made within a single image or between multiple images over time to detect potential conditions requiring response. In this manner, efficiency and effectiveness of many previously manually-implemented tasks may be improved.

Abstract: Techniques for indexing multimedia data substantially concurrently or contemporaneously with its capture to convert a real world event into an accessible database in real time are provided. The present invention introduces a new paradigm of converting a real world event in real time into a rich multimedia database by processing data from multiple sensors observing the event. Real time analysis of the sensor data, coupled with domain knowledge, results in instant indexing of multimedia data at capture time itself. This yields the semantic information to answer complex queries about the content, and the ability to extract portions of data that correspond to complex actions performed in the real world.

Abstract: Techniques for retrieval of multimedia data through visual representations are provided. Such visual representations, preferably in the form of visual activity maps or spatio-temporal activity maps, serve as an efficient and intuitive graphical user interface for multimedia retrieval, particularly when the media streams are derived from multiple sensors observing a physical environment. An architecture for interactive media retrieval is also provided by combining such visual activity maps with domain specific event information. Visual activity maps are derived from the trajectories of motion of objects in the environment. The visual activity map based techniques significantly help users in quickly and effectively discovering interesting portions of the data, and randomly accessing and retrieving the corresponding portions of the media streams.

Abstract: A method and apparatus for tracking an object using one or more video cameras together with a plurality of microphones and/or geophones, whereby accurate tracking of the object can be obtained even when the object changes directions as a result of an impact. A tennis ball may be tracked during a tennis match. Prior to and after an impact, the ball is tracked with the use of video cameras, illustratively in accordance with the method disclosed in U.S. Pat. No. 6,233,007. Then, the position of the ball at racket or ground impact is accurately determined by measuring the acoustical waves generated by the ball hitting the racket and/or either the acoustic waves or the elastic (Rayleigh) waves generated by the ball hitting the ground, respectively. Tracking then advantageously continues with use of the video cameras.

Abstract: Techniques for intelligent and automatic control of sensors for capturing data associated with real time events. Preferably, the sensors are associated with a multimedia database system. For example, a technique for controlling one or more sensors used to capture data associated with an event comprises the following steps/operations. First, sensor data captured in accordance with the event is processed. Then, the one or more sensors are automatically controlled based on information pertaining to the continual activity of at least one of one or more objects and one or more persons associated with the event in real time obtained using at least a portion of the processed data captured in accordance with the event.

Abstract: A method and apparatus for tracking an object using one or more video cameras together with a plurality of microphones and/or geophones, whereby accurate tracking of the object can be obtained even when the object changes directions as a result of an impact. A tennis ball may be tracked during a tennis match. Prior to and after an impact, the ball is tracked with the use of video cameras, illustratively in accordance with the method disclosed in U.S. Pat. No. 6,233,007. Then, the position of the ball at racket or ground impact is accurately determined by measuring the acoustical waves generated by the ball hitting the racket and/or either the acoustic waves or the elastic (Rayleigh) waves generated by the ball hitting the ground, respectively. Tracking then advantageously continues with use of the video cameras.

Abstract: Techniques for indexing multimedia data substantially concurrently or contemporaneously with its capture to convert a real world event into an accessible database in real time are provided. The present invention introduces a new paradigm of converting a real world event in real time into a rich multimedia database by processing data from multiple sensors observing the event. Real time analysis of the sensor data, coupled with domain knowledge, results in instant indexing of multimedia data at capture time itself. This yields the semantic information to answer complex queries about the content, and the ability to extract portions of data that correspond to complex actions performed in the real world.

Abstract: Techniques for retrieval of multimedia data through visual representations are provided. Such visual representations, preferably in the form of visual activity maps or spatio-temporal activity maps, serve as an efficient and intuitive graphical user interface for multimedia retrieval, particularly when the media streams are derived from multiple sensors observing a physical environment. An architecture for interactive media retrieval is also provided by combining such visual activity maps with domain specific event information. Visual activity maps are derived from the trajectories of motion of objects in the environment. The visual activity map based techniques significantly help users in quickly and effectively discovering interesting portions of the data, and randomly accessing and retrieving the corresponding portions of the media streams.