Abstract: Systems and methods for training and using machine learning models to classify vehicles from highway radar systems are provided. The training systems may use auxiliary radar processing to separate events by lane, length, and/or speed, and then use separate event data groups pooled from similar or proximate lanes, lengths, and/or speeds to train multiple models. At estimation time, incoming events may be grouped using similar groupings as those used during training to select which model to use. An incoming event may be applied to the neural network operations of the selected model to generate an estimate. Generating an estimate may involve successive applications of multiple linear convolutions and other steps along varying or alternating dimensions of the in-process data.

Abstract: Systems and methods for training and using machine learning models to classify vehicles from highway radar systems are provided. The training systems may use auxiliary radar processing to separate events by lane, length, and/or speed, and then use separate event data groups pooled from similar or proximate lanes, lengths, and/or speeds to train multiple models. At estimation time, incoming events may be grouped using similar groupings as those used during training to select which model to use. An incoming event may be applied to the neural network operations of the selected model to generate an estimate. Generating an estimate may involve successive applications of multiple linear convolutions and other steps along varying or alternating dimensions of the in-process data.

Abstract: A system using face and iris image capture for recognition of people. The system may have wide field-of-view, medium field-of-view and narrow field-of-view cameras to capture images of a scene of people, faces and irises for processing and recognition. Matching of the face and iris images with images of a database may be a basis for recognition and identification of a subject person.

Abstract: A system using face and iris image capture for recognition of people. The system may have wide field-of-view, medium field-of-view and narrow field-of-view cameras to capture images of a scene of people, faces and irises for processing and recognition. Matching of the face and iris images with images of a database may be a basis for recognition and identification of a subject person.

Abstract: A combination of inter-frame and intra-frame and sequential classification methods provide for robust and flexible object classification. Intra-frame classification determines the object type based on features extracted from a single image. Inter-frame classification determines object types based on the features extracted from several sequential frames. A sequential classification combines the results of the inter- and intra-frame classifications over a sequence of images.

Abstract: The present invention pertains to video playback systems, devices and methods for searching events contained within a video image sequence. A video playback system in accordance with an illustrative embodiment of the present invention includes a video playback device adapted to run a sequential searching algorithm for sequentially presenting video images within an image sequence, and a user interface that can be used by an operator to detect the occurrence of an event contained within the image sequence. Methods of searching for an event of interest contained within an image sequence are also disclosed herein.

Abstract: Methods and systems for packaging video sequences based on user-specified events are described herein. An illustrative method of event-packaging a video sequence may include the steps of acquiring a video stream containing an event of interest, extracting various event information from the video stream and storing one or more event parameters within an event database, extracting a video clip from the video stream containing the event of interest, associating metadata representing the event parameters to the video clip, and exporting the video clip containing the event of interest and associated metadata to an external agent. In certain embodiments, a video image-processing appliance manager and/or one or more appliance modules can be provided to automatically extract event information from the acquired video stream, and to manage the indexing and storage of event parameters within the event database.

Abstract: A video monitoring system including a video image-processing appliance manager adapted to provide an interface for one or more monitoring devices is disclosed. A video monitoring system in accordance with an illustrative embodiment of the present invention may include a host application including one or more monitoring devices, a video image-processing appliance manager called by the host application, and one or more appliance modules called by the appliance manager and adapted to run a number of video image-processing algorithms or routines that can be used to detect the occurrence of events within a region of interest. Methods of interfacing with one or more monitoring devices within a video monitoring network are also disclosed herein.

Abstract: Methods and systems for defining, detecting, analyzing, indexing, and retrieving events using video image processing techniques are described herein. An illustrative method of detecting and analyzing events occurring within a region of interest of a video monitoring system may include the steps of extracting information regarding one or more objects located within a region of interest, analyzing the extracted information to detect the occurrence of one or more events within the region of interest, matching at least one of the detected events with a corresponding user-specified event, and performing an action response upon the detection of such an event. In certain embodiments, the detected events may be defined as a set of semantic parameters relating to the object's state and/or physical features, which can be compared against a corresponding set of semantic parameters programmed within a video image-processing appliance manager.