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: Systems and methods are provided for real time dynamic triggering of a conspicuous signal for a vehicle on a path of travel. A sensor array detects environmental factors presenting a predetermined risk to the vehicle. A decision module assesses the environmental factors and the associated risks and determines if the conspicuousness signal is warranted and a type of signal to be made. An actuating module actuates the conspicuousness signal based on the determining of the decision module.

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: A method for automatically determining a dynamic queue configuration includes acquiring a series of frames from an image source surveying a queue area. The method includes detecting at least one subject in a frame. The method includes tracking locations of each detected subject across the series of frames. The method includes generating calibrated tracking data by mapping the tracking locations to a predefined coordinate system. The method includes localizing a queue configuration descriptor based on the tracking data.

Abstract: A system and method for detecting electronic device use by a driver of a vehicle including acquiring an image including a vehicle from an associated image capture device positioned to view oncoming traffic, locating a windshield region of the vehicle in the captured image, processing pixels of the windshield region of the image for computing a feature vector describing the windshield region of the vehicle, applying the feature vector to a classifier for classifying the image into respective classes including at least classes for candidate electronic device use and candidate electronic device non-use, and outputting the classification.

Abstract: Systems, methods, apparatus, and computer-implemented methods are provided for determining a camera calibration. The method includes accessing video data for a geographic area captured by a video camera. The video data is processed to detect a plurality of moving vehicles in the video data. A detection area is defined based on the plurality of moving vehicles. A plurality of line segments are identified for each of the plurality of vehicles detected in the video data. A plurality of vanishing points are estimated based on at least a subset of the plurality of line segments. A camera calibration is determined based on the plurality of vanishing points.

Abstract: This disclosure provides a method and system to detect a predefined activity, e.g., vandalism, loitering, trespass, etc., associated with a parked vehicle. According to an exemplary embodiment, a method includes capturing video of a parking area and processing the video to detect vandalism and/or loitering with respect to a region of interest associated with the parked vehicle.

Abstract: Systems and methods are disclosed for background modeling in a computer vision system for enabling foreground object detection. A video acquisition model receives video data from a sequence of frames. A fit test module identifies a foreground object from the video data and defines a foreground mask representative of the identified foreground object. A foreground-aware background estimation module defines a first background model from the video data and then further defines an updated background model from an association of a current frame of the video data, the first background model and the foreground mask.

Abstract: A system and method for creating a spatiotemporal image representation with information content that enables accurate and rapid processing for several applications.

Abstract: A method for gait analysis of a subject performed periodically over time to detect changes in one or more gait characteristics. The method includes detecting and identifying a subject and analyzing the gait of the subject on a plurality of occasions. Analyzing the gait of the subject includes, a detecting body parts, generating a joint model depicting the location of the at least one joint in each of the at least two frames, using the joint model to segment a gait cycle for the at least one joint, and comparing the gait cycle to a threshold value to detect abnormal gait.

Abstract: A computer-implemented method for gait analysis of a subject includes obtaining visual data from an image capture device positioned in front of or behind the subject, the visual data comprising at least two image frames of the subject over a period of time walking toward or away from the image capture device, the at least two image frames capturing at least a portion of the gait of the subject, detecting within the at least two images body parts as two-dimensional landmarks using a pose estimation algorithm on each of the at least two frames, generating a joint model depicting the location of the at least one joint in each of the at least two frames, using the joint model to segment a gait cycle for the at least one joint, and comparing the gait cycle to a threshold value to detect abnormal gait.

Abstract: A computer-implemented system and method for gait analysis of a subject. The method includes obtaining visual data from an image capture device positioned in front of or behind the subject, the plurality of image frames capturing at least one gait cycle of the gait of the subject, detecting one or more prescribed features within the plurality of image frames, analyzing each of the plurality of image frames to detect cross-frame stability of the one or more prescribed features, and segmenting the gait of the subject into at least one gait cycle based at least in part on the detected cross-frame stability of the one or more prescribed features.

Abstract: A system and method for detecting electronic device use by a driver of a vehicle including acquiring an image including a vehicle from an associated image capture device positioned to view oncoming traffic, locating a windshield region of the vehicle in the captured image, processing pixels of the windshield region of the image for computing a feature vector describing the windshield region of the vehicle, applying the feature vector to a classifier for classifying the image into respective classes including at least classes for candidate electronic device use and candidate electronic device non-use, and outputting the classification.

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 for assessing patient movement for Parkinson's disease includes capturing a video of a subject performing a finger tapping sequence comprising a predetermined number of open and close periods. According to an exemplary embodiment, a system and method includes extracting a region of interest for each frame of the video and generating a projection of the region of interest for each frame of the video using perpendicular vector projections in a direction or plurality of directions.

Abstract: A method for detecting a vehicle running a stop signal includes acquiring at least two evidentiary images of a candidate violating vehicle captured from at least one camera monitoring an intersection. The method includes extracting feature points in each of the at least two evidentiary images. The method includes computing feature descriptors for each of the extracted feature points. The method includes determining a correspondence between feature points having matching feature descriptors at different locations in the at least two evidentiary images. The method includes extracting at least one attribute for each correspondence. The method includes determining if the candidate violating vehicle is in violation of running the stop signal using the extracted attribute.

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: A method for detecting a vehicle running a stop signal positioned at an intersection includes acquiring a sequence of frames from at least one video camera monitoring an intersection being signaled by the stop signal. The method includes defining a first region of interest (ROI) including a road region located before the intersection on the image plane. The method includes searching the first ROI for a candidate violating vehicle. In response to detecting the candidate violating vehicle, the method includes tracking at least one trajectory of the detected candidate violating vehicle across a number of frames. The method includes classifying the candidate violating vehicle as belonging to one of a violating vehicle and a non-violating vehicle based on the at least one trajectory.

Abstract: A spatiotemporal system and method for parking occupancy detection. The system can generally include suitable image acquisition, processing, transmission and data storage devices configured to carry out the method which includes generating and processing spatiotemporal images to detect the presence of an object in a region of interest, such as a vehicle in a parking stall.

Abstract: A system and method for object tracking and timing across multiple camera views includes local and global tracking modules for tracking the location of objects as they traverse particular regions of interest within an area of interest. A local timing module measures the time spent with each object within the area captured by a camera. A global timing module measures the time taken by the tracked object to traverse the entire area of interest or the length of the stay of the object within the area of interest.