Abstract: When monitoring a workspace to determine whether scheduled tasks or chores are completed according to a predetermined schedule, a video monitoring system monitors a region of interest (ROI) to identify employee-generated signals representing completion of a scheduled task. An employee makes a mark or gesture in the ROI monitored by the video monitoring system and the system analyzes pixels in each captured frame of the ROI to identify an employee signal, map the signal to a corresponding scheduled task, update the task as having been completed upon receipt of the employee signal, and alert a manager of the facility as to whether the task has been completed or not.

Abstract: A system and method to identify the leader of a group in a retail, restaurant, or queue-type setting (or virtually any setting) through recognition of payment gestures. The method comprises acquiring initial video of a group, developing feature models for members of the group, acquiring video at a payment location, identifying a payment gesture in the acquired video, defining the person making the gesture as the leader of the group, and forwarding/backtracking through the video to identify timings associated with leader events (e.g., entering, exiting, ordering, etc.).

Abstract: Disclosed is a method and system for detecting an interaction event between two or more objects in a surveillance area, via the application of heuristics to trajectory representations of the static or dynamic movements associated with the objects. According to an exemplary embodiment, trajectory interaction features (TIFs) are extracted from the trajectory representations and heuristics are applied to the TIFs to determine if an interaction event has occurred, such as a potential illegal drug deal involving at least one pedestrian and at least one vehicle.

Abstract: A system for recognizing processes performed by a call center agent during a session may receive input data from a screen recording system that includes a video signal representing a plurality of frames from a time-series video recording or video stream of a desktop of a user electronic device. The system processes the video signal to identify one or more frames of interest from the plurality of frames. Each frame of interest includes a change in a layout of the corresponding one or more screens as compared to a preceding frame in the time-series video recording. The system automatically identifies actions performed by the call center agent that represent an interaction that the call center agent had with one or more screens corresponding to the frame of interest. The system generates an event log that includes a timeline depicting a visual representation of the identified actions.

Abstract: A system for recognizing processes performed by a call center agent during a session may receive input data from a screen recording system that includes a video signal representing a plurality of frames from a time-series video recording or video stream of a desktop of a user electronic device. The system processes the video signal to identify one or more frames of interest from the plurality of frames. Each frame of interest includes a change in a layout of the corresponding one or more screens as compared to a preceding frame in the time-series video recording. The system automatically identifies actions performed by the call center agent that represent an interaction that the call center agent had with one or more screens corresponding to the frame of interest. The system generates an event log that includes a timeline depicting a visual representation of the identified actions.

Abstract: Disclosed is a method and system for detecting an interaction event between two or more objects in a surveillance area, via the application of heuristics to trajectory representations of the static or dynamic movements associated with the objects. According to an exemplary embodiment, trajectory interaction features (TIFs) are extracted from the trajectory representations and heuristics are applied to the TIFs to determine if an interaction event has occurred, such as a potential illegal drug deal involving at least one pedestrian and at least one vehicle.

Abstract: A system for recognizing processes performed by a call center agent during a session may collect input data by initiating a screen capture logging thread to capture screen shots of a desktop of the electronic device during a session. The system analyzes the input data to generate one or more events, generates a mid-level event log comprising one or more of the events, and performs action recognition on the mid-level event log to ascertain one or more actions that were performed within the one or more graphical user interfaces by the call center agent during the session.

Abstract: This disclosure provides a method and system for automatically recognizing facial expressions at variable resolutions of video. According to one exemplary method, facial expressions are detected, extracted and classified from a video sequence based on an automatic localization of the periocular region associated with a detected and extracted face.

Abstract: Disclosed is a method and system for detecting an interaction event between two or more objects in a surveillance area, via the application of heuristics to trajectory representations of the static or dynamic movements associated with the objects. According to an exemplary embodiment, trajectory interaction features (TIFs) are extracted from the trajectory representations and heuristics are applied to the TIFs to determine if an interaction event has occurred, such as a potential illegal drug deal involving two or more pedestrians.

Abstract: Disclosed is a method and system for detecting an interaction event between two or more objects in a surveillance area via the application of heuristics to trajectory representations of the static or dynamic movements associated with the objects. According to an exemplary embodiment, trajectory interaction features (TIFs) are extracted from the trajectory representations and heuristics are applied to the TIFs to determine if an interaction event has occurred, such as a potential mugging involving two or more pedestrians.

Abstract: Disclosed is a method and system for detecting an interaction event between two or more objects in a surveillance area via the application of heuristics to trajectory representations of the static or dynamic movements associated with the objects. According to an exemplary embodiment, trajectory interaction features (TIFs) are extracted from the trajectory representations and heuristics are applied to the TIFs to determine if an interaction event has occurred, such as a potential mugging involving two or more pedestrians.

Abstract: A system for recognizing processes performed by a call center agent during a session collects from one or more input devices in communication with the electronic device, input data that includes data pertaining to one or more interactions that a call center agent has with one or more programs running on the electronic device that cause one or more graphical user interfaces to be displayed on a desktop of the electronic device during a session. The system analyzes the input data to generate one or more events and a mid-level event log having one or more of the events, and performs action recognition on the mid-level event log to ascertain one or more actions that were performed within the one or more graphical user interfaces by the call center agent during the session.

Abstract: A computer vision system (100) operates to monitor an environment (e.g., such as a restaurant, store or other retail establishment) including a resource located therein (e.g., such as a restroom, a dining table, a drink, condiment or supply dispenser, a trash receptacle or a tray collection rack). The system includes: an image source or camera (104) that supplies image data (130) representative of at least a portion of the environment monitored by the system, the portion including the resource therein; and an event detection device (102) including a data processor (112) and operative to detect an event involving the resource. Suitably, the event detection device is arranged to: (i) be selectively configurable by a user to define the event involving the resource; (ii) receive the image data supplied by the image source; (iii) analyze the received image data to detect the defined event; and (iv) output a notification in response to detecting the defined event.

Abstract: Disclosed is a method and system for detecting an interaction event between two or more objects in a surveillance area, via the application of heuristics to trajectory representations of the static or dynamic movements associated with the objects. According to an exemplary embodiment, trajectory interaction features (TIFs) are extracted from the trajectory representations and heuristics are applied to the TIFs to determine if an interaction event has occurred, such as a potential illegal drug deal involving two or more pedestrians.

Abstract: This disclosure provides a method and system for automatically recognizing facial expressions at variable resolutions of video. According to one exemplary method, facial expressions are detected, extracted and classified from a video sequence based on an automatic localization of the periocular region associated with a detected and extracted face.

Abstract: A system and method of monitoring a region of interest comprises obtaining visual data comprising image frames of the region of interest over a period of time, analyzing individual subjects within the region of interest, the analyzing including at least one of tracking movement of individual subjects over time within the region of interest or extracting an appearance attribute of the individual subjects, and defining a group to include individual subjects having at least one of similar movement profiles or similar appearance attributes. The tracking movement includes detecting at least one of a trajectory of an individual subject within the region of interest, a dwell of an individual subject in at least one location within the region of interest, or an entrance or exit location within the region of interest.

Abstract: This disclosure provides a method and system for automatically recognizing facial expressions at variable resolutions of video. According to one exemplary method, facial expressions are detected, extracted and classified from a video sequence based on an automatic localization of the periocular region associated with a detected and extracted face.

Abstract: This disclosure provides a video-based method and system for busyness detection and notification. Specifically, according to an exemplary embodiment, multiple overhead image capturing devices are used to acquire video including multiple non-overlapping ROIs (regions of interest) and the video is processed to count the number of people included within the ROIs. A busyness metric is calculated based on the number of people counted and notification of the busyness metric or changes in the busyness metric is communicated to appropriate personnel, e.g., a manager of a retail store.

Abstract: A system for delivering one of a good and service to a customer in a retail environment includes a computer located at an order station. The computer is configured to receive an order for the one good and service. The system includes a first image capture device in communication with the computer. The first image capture device captures a first image of a customer ordering the one good and service in response to the order being submitted. The system further includes a wearable computer peripheral device configured to acquire the first image from the first image capture device and electronically display the first image to a user tasked with delivering the one good and service while carrying the second wearable computer peripheral device. In this manner, an identity of the customer can be compared against the first image upon a delivery of the one good and service.

Abstract: Disclosed are methods and systems to automatically detect and optionally classify when a recipient receives goods in surveillance video. According to one exemplary embodiment, a computer implemented method determines a customer has received goods which are associated with a retail environment.