Abstract:
A method of estimating one or more dimensions of a patch panel may include receiving an image of a patch panel that comprises a plurality of ports and one or more gaps, extracting, by a computing device, a region of interest from the received image, detecting, by the computing device, one or more line segments from the region of interest, determining whether one or more candidate ports can be identified based on at least a portion of the line segments, and in response to determining that one or more candidate ports can be identified, identifying one or more candidate ports, and determining, by the computing device, a gap length associated with the identified candidate ports.
Abstract:
A method and apparatus for obtaining an image and providing one or more document files to a user is disclosed. The method may include receiving an image of a target object using an imaging device, analyzing the image to identify one or more features, and accessing a model database to identify an object model having features that match the identified features from the image. When the system determines that more than one model may be a match, the method looks for distinguishing features of the target object and selects a model that includes the distinguishing features. The method then includes, retrieving a document file that corresponds to the identified model from a file database, and providing the document file to a user.
Abstract:
Images with respect to an object at an ordering, payment, and delivery locations can be captured utilizing an image capturing system. Capture can be after detecting the presence of the object at each location utilizing an object presence sensor. The captured image can be processed to associate it with a signature and can also be processed in order to extract a small region of interest (e.g., license plate) and can be reduced to a unique signature. Signature can be stored into a database together with the corresponding order and images. Signatures can be matched. The order associated with the object matched by the system together with at least one of the images captured at the delivery point and the order point can be displayed at a user interface located at the payment/delivery point to ensure that the right order is delivered to the right customer associated with the object.
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:
Methods and systems for detecting anomalies in transportation related video footage. In an offline training phase, receiving video footage of a traffic location can be received. Also, in an offline training phase, event encodings can be extracted from the video footage and collected or compiled into a training dictionary. One or more input video sequences captured at the traffic location or a similar traffic location can be received in an online detection phase. Then, an event encoding corresponding to the input video sequence can be extracted. The event encoding can be reconstructed with a low rank sparsity prior model applied with respect to the training dictionary. The reconstruction error between actual and reconstructed event encodings can then be computed in order to determine if an event thereof is anomalous by comparing the reconstruction error with a threshold.
Abstract:
Methods and systems for detecting anomalies in transportation related video footage. In an offline training phase, receiving video footage of a traffic location can be received. Also, in an offline training phase, event encodings can be extracted from the video footage and collected or compiled into a training dictionary. One or more input video sequences captured at the traffic location or a similar traffic location can be received in an online detection phase. Then, an event encoding corresponding to the input video sequence can be extracted. The event encoding can be reconstructed with a low rank sparsity prior model applied with respect to the training dictionary. The reconstruction error between actual and reconstructed event encodings can then be computed in order to determine if an event thereof is anomalous by comparing the reconstruction error with a threshold.
Abstract:
A method of estimating one or more dimensions of a patch panel may include receiving an image of a patch panel that comprises a plurality of ports and one or more gaps, extracting, by a computing device, a region of interest from the received image, detecting, by the computing device, one or more possible port edges from the region of interest, fitting the detected possible port edges to a cross-ratio constancy model to determine a port-to-gap-length ratio associated with the patch panel, using the port-length-to-gap-length ratio to determine a location of one or more final port edges, and determining a location of one or more final ports based on the location of the final port edges.
Abstract:
A method for processing an image of a patch panel includes: a) receiving an initial image; b) determining multiple ports of the patch panel are aligned in a desired orientation in the initial image; c) processing the initial image to identify edge lines perpendicular to the desired orientation; d) processing the edge lines to identify a port hypothesis that includes an estimated port gap between the multiple ports along the desired orientation and an estimated port size for the multiple ports along the desired orientation; e) processing the port hypothesis to determine an estimated port quantity for the multiple ports; and f) processing the port hypothesis to identify an estimation error between expected and detected edge line positions in relation to a reference axis perpendicular to the edge lines. An apparatus associated therewith includes an input/output and pre-processing modules and detection, hypothesis, estimating, and scoring processors.
Abstract:
Methods, systems, and processor-readable media for pruning a training dictionary for use in detecting anomalous events from surveillance video. Training samples can be received, which correspond to normal events. A dictionary can then be constructed, which includes two or more classes of normal events from the training samples. Sparse codes are then generated for selected training samples with respect to the dictionary derived from the two or more classes of normal events. The size of the dictionary can then be reduced by removing redundant dictionary columns from the dictionary via analysis of the sparse codes. The dictionary is then optimized to yield a low reconstruction error and a high-interclass discriminability.
Abstract:
A method and structure for estimating parking occupancy within an area of interest can include the use of at least two image capture devices and a processor (e.g., a computer) which form at least part of a network. A method for estimating the parking occupancy within the area of interest can include the use of vehicle entry and exit data from the area of interest, as well as an estimated transit time for vehicles transiting through the area of interest without parking.