Abstract: A method for detecting sitting behavior includes acquiring a sequence of frames capturing a scene-of-interest at an overhead view. The method includes detecting at least one empty seat within the scene-of-interest and associating the seat as being unoccupied and the frame as a reference frame. The method includes extracting reference features describing a region of the unoccupied seat in the reference frame and quantifying the reference features to form a reference feature vector. The method includes extracting features describing the region in a given frame and quantifying the features to form a current feature vector. The method includes measuring a change in a feature vector over time using the reference feature vector and the current feature vector. The method includes and determining a status of the seat in the given frame as being one of occupied and unoccupied based on the change in the feature vector.

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 system and method of video-based chew counting by receiving image frames from a video camera, determining feature points within the image frames from the video camera, generating a motion signal based on movement of the feature points across the image frames from the video camera, and determining a chew count based on the motion signal.

Abstract: A system and method for monitoring parking and identifying vehicles by monitoring a parking region based on video data of the parking region received from a video camera, detecting a parking event associated with a vehicle in the parking region, adjusting a view of the video camera based on the parking event, physically tracking the vehicle using the video camera, capturing an image of a license plate of the vehicle, and resuming monitoring the parking region after capturing the image of the license plate.

Abstract: A method for detecting parking occupancy includes receiving video data from a sequence of frames taken from an associated image capture device monitoring a parking area. The method includes determining at least one candidate region in the parking area. The method includes comparing a size of the candidate region to a size threshold. In response to size of the candidate region meeting and exceeding the size threshold, the method includes determining whether the candidate region includes one of at least one object and no objects. The method includes classifying at least one object in the candidate region as belonging to one of at least two vehicle-types. The method further includes providing vehicle occupancy information to a user.

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: A system for estimating parking occupancy includes a vehicle-detection device including an adjustable mast supporting an image capture device at a select height. The image capture device acquires video of a current parking area. A computer processor in communication with the image capture device is configured to receive the video data and define a region of interest in the video data. The processor is further configured to perform a spatial transform on the ROI to transform the ROI to a normalized geometric space. The processor is further configured to apply features of a detected object in the normalized geometric space to a vehicle classifier—previously trained with samples acquired from a normalized camera perspective similar to the normalized geometric space—and determine the occupancy of the current parking area using an output of the classifier.

Abstract: A method for detecting settle-down time in a space includes acquiring a sequence of frames capturing a select space from a first camera. The method includes determining an initial time for computing a duration it takes for an associated occupant to settle into a seat in the select space. The method includes determining one or more candidate frames from the sequence of frames where one or both of a sitting behavior and seat occupancy is observed at the seat. The method includes determining a final frame and a final time associated with the final frame from the one or more candidate frames. The method includes computing the settle-down time using the initial and the final times.

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 sitting behavior includes acquiring a sequence of frames capturing a scene-of-interest at an overhead view. The method includes detecting at least one empty seat within the scene-of-interest and associating the seat as being unoccupied and the frame as a reference frame. The method includes extracting reference features describing a region of the unoccupied seat in the reference frame and quantifying the reference features to form a reference feature vector. The method includes extracting features describing the region in a given frame and quantifying the features to form a current feature vector. The method includes measuring a change in a feature vector over time using the reference feature vector and the current feature vector. The method includes and determining a status of the seat in the given frame as being one of occupied and unoccupied based on the change in the feature vector.

Abstract: A system and method for detecting a seat belt violation in a vehicle. The method may include receiving an image including a region of interest where a seat belt is visible if the seat belt is buckled. One or more first features may be extracted from the image. The one or more first features may be compared to one or more second features extracted from a plurality of sample images. It may be determined whether the seat belt is buckled in the image based upon the comparison.

Abstract: This disclosure provides methods and systems of classifying a vehicle using motion vectors associated with captured images including a vehicle. According to an exemplary method, a cluster of motion vectors representative of a vehicle within a target region is analyzed to determine geometric attributes of the cluster and/or measure a length of a detected vehicle, which provides a basis for classifying the detected vehicle.

Abstract: A method for removing false foreground image content in a foreground detection process performed on a video sequence includes, for each current frame, comparing a feature value of each current pixel against a feature value of a corresponding pixel in a background model. The each current pixel is classified as belonging to one of a candidate foreground image and a background based on the comparing. A first classification image representing the candidate foreground image is generated using the current pixels classified as belonging to the candidate foreground image. The each pixel in the first classification image is classified as belonging to one of a foreground image and a false foreground image using a previously trained classifier. A modified classification image is generated for representing the foreground image using the pixels classified as belonging to the foreground image while the pixels classified as belonging to the false foreground image are removed.

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: An automated method and system for detecting the presence of a smoking product utilizing a near infrared video-processing unit in real time. One or more near infrared (NIR) video capturing units can be configured to capture a video feed. The video feed can be processed by the video-processing unit in order to detect a smoking product (e.g., a lit cigarette) within a field of view of the video capturing unit. A near infrared video sequence can be read and analyzed for the presence of a “hot spot” of a predetermined size based on pixel color information. In some cases, the motion of the hot spot can be tracked in response to the detection of the hot spot. An alarm signal can also be triggered in some cases, if the pattern of motion is consistent with that of a cigarette being smoked.

Abstract: A system and method of monitoring a customer space including obtaining visual data comprising image frames of the customer space over a period of time, defining a region of interest within the customer space, the region of interest corresponding to a portion of the customer space in which customers relocate objects, monitoring the region of interest for at least one predefined clutter condition, and generating a notification when the at least one predefined clutter condition is detected.

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 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: When performing video-based speed enforcement a main camera and a secondary RGB traffic camera are employed to provide improved accuracy of speed measurement and improved evidentiary photo quality compared to single camera approaches. The RGB traffic camera provides sparse secondary video data at a lower cost than a conventional stereo camera. The sparse stereo processing is performed using the main camera data and the sparse RGB camera data to estimate a height of one or more tracked vehicle features, which in turn is used to improve speed estimate accuracy. By using secondary video, spatio-temporally sparse stereo processing is enabled specifically for estimating the height of a vehicle feature above the road surface.

Abstract: When restoring a scanned halftone image of a damaged document, parameters of the halftone structure (geometry) are estimated, as is an intended contone gray level for damaged portions of the image. Locations of halftone cell tiles in the scanned image are determined based on the halftone structure, and a halftone profile model is generated using the estimated halftone parameters and contone information. Image segments are aligned using global features for coarse alignment and halftone structure for fine alignment, such as in cases where the scanned halftone image contains unconnected fragments. Missing parts of the damaged document image are filled in using the halftone profile model and estimated contone values.