Abstract: A method for detecting a double-parked vehicle includes identifying a parking region in video data received from an image capture device monitoring the parking region. The method includes defining an enforcement region at least partially surrounding the parking region. The method includes detecting a stationary vehicle in the enforcement region. The method includes determining the occurrence of an event relative to the stationary vehicle. In response to the determined occurrence of the event, the method includes classifying the stationary vehicle as being one of double parked and not double parked.

Abstract: Managing power consumption of multiple computing node clusters of a computing rack system is described. An example system may include a plurality of computing node clusters each comprising a respective plurality of computing nodes, and a power management system. The power management system is configured to determine respective power budget rules associated with each of the plurality of computing node clusters based on a maximum power consumption limit, and to provide the respective power budget rules to an associated one of the plurality of computing node clusters. The power management system is further configured to receive respective power consumption data from each of the plurality of computing node clusters and to adjust the respective power budget rules associated with at least one of the plurality of computing node clusters based on the respective power consumption data associated with each of the plurality of computing node clusters.

Abstract: Managing power consumption of multiple computing node clusters of a computing rack system is described. An example system may include a plurality of computing node clusters each comprising a respective plurality of computing nodes, and a power management system. The power management system is configured to determine respective power budget rules associated with each of the plurality of computing node clusters based on a maximum power consumption limit, and to provide the respective power budget rules to an associated one of the plurality of computing node clusters. The power management system is further configured to receive respective power consumption data from each of the plurality of computing node clusters and to adjust the respective power budget rules associated with at least one of the plurality of computing node clusters based on the respective power consumption data associated with each of the plurality of computing node clusters.

Abstract: A hyper-converged computing system may include multiple computing nodes and a power management system. Each computing node may have a processor operating at a power state. Each computing node may receive a power budget from the power management system, determine an instant power consumption in the node and determine whether the instant power consumption is approaching the power budget. If the instant power consumption is approaching the power budget, the computing node may adjust the power consumption of the node. The power management system may determine an initial power budget rule for each computing node and transmit the initial power budget rule to each respective computing node. The power management system may also obtain various provisioning and status from the multiple computing nodes and use the provisioning and status to update the power budget rules for each respective computing node.

Abstract: Methods and systems for preventing vehicle theft. A video stream of a parking area wherein a vehicle is parked can be captured, the video stream provided by a theft notification service to which the vehicle is pre-registered. The vehicle in the video stream can be identified. The video stream is then analyzed to detect motion with respect to the vehicle. An alert can then be generated if motion is detected.

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: Methods and devices send, from an application to an image processor, an identity of a vehicle parking space and/or an identity of a vehicle parked in the vehicle parking space. Such methods and devices obtain an image of the parked vehicle, using a fixed camera, and send the image to the image processor. These methods and devices then confirm the identity of the vehicle parked in the vehicle parking space, and send a confirmation to the application. These methods and devices display the confirmation on the graphic user interface of the user portable computing device (using the application). These methods and devices automatically end the timed payment session for the vehicle parking space based on images of the scene obtained through the camera showing the identified vehicle not occupying the vehicle parking space, using the image processor.

Abstract: Methods, systems and processor-readable media for portable parking occupancy detection. One or more cameras can be provided on a portable mast for capturing video on parking of a street. Optional attachments to the portable mast can include stabilization base and/or a set of guy ropes for further stabilizing the mast. A power unit can be utilized for delivering power to the system. A video capturing/processing unit either captures and records the video from the camera(s) for offline processing of parking occupancy or processes the videos on-site. Optionally, a wireless communication unit for transmitting either video or processed parking occupancy data to a central location can be employed.

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 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 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: Methods and systems for training a parked vehicle detector. Video data regarding one or more parking sites can be captured. Positive training samples can then be collected from the video data based on a combination of one or more automated computing methods and human-input auxiliary information. Additionally, negative training samples can be collected from the video data based on automated image analyses with respect to the captured video data. The positive training samples and the negative training samples can then be used to train, re-train or update one or more parked vehicle detectors with respect to the parking site(s) for use in managing parking at the parking site(s).

Abstract: What is disclosed is a system and method for processing image data acquired using a multi-band infrared camera system with a spectral mosaic filter arranged in a geometric pattern without having to perform a demosaicing that is typical with processing data from an array of sensors. In one embodiment, image data that has been captured using a camera system that has a spectral filter mosaic comprising a plurality of spectral filters arrayed on a grid. A material index is determined, using intensity values collected by sensor elements associated with a cell's respective spectral filters. All of the material indices collectively generate a material index image. Thereafter, material identification is performed on the material index image using, for example, pixel classification. Because the demosaicing step can be effectively avoided, image processing time is reduced. The teachings hereof find their uses in a wide array of applications including automated HOV/HOT violation detection.

Abstract: This disclosure provides vehicle detection methods and systems including irrelevant search window elimination and/or window score degradation. According to one exemplary embodiment, provided is a method of detecting one or more parked vehicles in a video frame, wherein candidate search windows are limited to one or more predefined window shapes. According to another exemplary embodiment, the method includes degrading a classification score of a candidate search window based on aspect ratio, window overlap area and/or a global maximal classification.

Abstract: A method for training a vehicle detection system used in a street occupancy estimation of stationary vehicles. The method includes defining first and second areas on an image plane of an image capture device associated with monitoring for detection of vehicles. The method includes receiving video-data from a sequence of frames captured from the image capture device. The method includes determining candidate frames that include objects relevant to a classification task in the second area. The method includes extracting the objects from the candidate frames, extracting features of each extracted object, and assigning labels to the each extracted object. The method includes training at least one classifier using the labels and extracted features. The method includes using the at least one trained classifier to classify a stationary vehicle detected in the first area.

Abstract: A method for determining parking availability includes receiving video data from a sequence of frames taken from an image capture device monitoring a parking area. The method includes detecting at least one object located in the parking area. The method includes determining boundaries of the parking area. The boundaries include at least an inner boundary relative to the image capture device and an outer boundary relative to the image capture device. The outer boundary is substantially parallel to the inner boundary. The method further includes computing a length of at least one of the object and a space between objects using an object pixel for each of the inner and outer boundaries. Using the computed length, The method includes determining a parking availability in the parking area. The method includes outputting a notice of the parking availability to a user.

Abstract: Methods and devices send, from an application to an image processor, an identity of a vehicle parking space and/or an identity of a vehicle parked in the vehicle parking space. Such methods and devices obtain an image of the parked vehicle, using a fixed camera, and send the image to the image processor. These methods and devices then confirm the identity of the vehicle parked in the vehicle parking space, and send a confirmation to the application. These methods and devices display the confirmation on the graphic user interface of the user portable computing device (using the application). These methods and devices automatically end the timed payment session for the vehicle parking space based on images of the scene obtained through the camera showing the identified vehicle not occupying the vehicle parking space, using the image processor.

Abstract: A method and system for determining one or more dimension estimations for a vehicle. A sequence of image frames of a vehicle is received, and a digital representation of the vehicle is extracted from each image in the sequence of image frames. A bounding box is determined for the vehicle based upon the extracted digital representation for each digital representation of the vehicle and at least one dimension of the vehicle is estimated based upon the determined bounding box. An indication of the at least one estimated dimension is output. The indication of at least one estimated dimension is transferred as an input to a comparison technique for further processing the indication of the at least one estimated dimension. The comparison technique can include a parking determination process configured to determine a recommended spot for the vehicle based upon the indication of the at least one estimated dimension.

Abstract: A method and a system for automating parking payment includes receiving video data in a sequence of frames provided by a video capture device observing a parking area. The method includes detecting a vehicle in the parking area using the video data. The method further includes receiving information of a vehicle in the parking area provided by a user device. The method includes comparing the characteristics of the detected vehicle with the information from the user device. In response to the characteristics of the detected vehicle being a match to the information sent from the user device, the method includes tracking the detected vehicle across the sequence of frames. The method includes computing a duration that the detected vehicle remains stationary using the tracking. The method includes computing an amount for charging the associated user device based on the duration.

Abstract: Systems and methods for aiding on-street parking occupancy detection from a moving device, such as, for example, an automotive vehicle, a bicycle, etc. An optimized route(s) can be pre-selected for scheduling the moving device from one street block to another. A display device displays where the moving device is at the time on the optimized route and selects, for example, the street block, and a recording device that records parking occupancy data. In some embodiments, a GPS module can be provided, which communicates with the recording device to assist in determining the location of the parking occupancy data.