Abstract: Disclosed herein is an object detection system, including apparatuses and methods for object detection. An implementation may include receiving a first class of a first object depicted in an image frame from a classification model and subsequently receiving a second image frame. The implementation further includes predicting, using a classification tracking model, that the classification model will output the first class for the second image frame and then detecting whether the first class is in fact outputted. The implementation includes determining that the second image frame should be added to a training dataset for the classification model when detecting that the classification model did not generate the first class for the second image frame as predicted and re-training the classification model using the training dataset.

Abstract: Disclosed herein is an object detection system, including apparatuses and methods for object detection. An implementation may include receiving a first image frame from an ROI detection model that generated a first ROI boundary around a first object detected in the first image frame and subsequently receiving a second image frame. The implementation further includes predicting, using an ROI tracking model, that the first ROI boundary will be present in the second image frame and then detecting whether the first ROI boundary is in fact present in the second image frame. The implementation includes determining that the second image frame should be added to a training dataset for the ROI detection model when detecting that the ROI detection model did not generate the first ROI boundary in the second image frame as predicted and re-training the ROI detection model using the training dataset.

Abstract: Disclosed herein is an object detection system, including apparatuses and methods for object detection. An implementation may include receiving a first image frame from an ROI detection model that generated a first ROI boundary around a first object detected in the first image frame and subsequently receiving a second image frame. The implementation further includes predicting, using an ROI tracking model, that the first ROI boundary will be present in the second image frame and then detecting whether the first ROI boundary is in fact present in the second image frame. The implementation includes determining that the second image frame should be added to a training dataset for the ROI detection model when detecting that the ROI detection model did not generate the first ROI boundary in the second image frame as predicted and re-training the ROI detection model using the training dataset.

Abstract: A building radar-camera system includes a camera configured to capture one or images, the one or more images including first locations within the one or more images of one or more points on a world-plane and a radar system configured to capture radar data indicating second locations on the world-plane of the one or more points. The system includes one or more processing circuits configured to receive a correspondence between the first locations and the second locations of the one or more points, generate a sphere-to-plane homography, the sphere-to-plane homography translating between points captured by the camera modeled on a unit-sphere and the world-plane based on the correspondence between the first locations and the second locations, and translate one or more additional points captured by the camera or captured by the radar system between the unit-sphere and the world-plane based on the sphere-to-plane homography.

Abstract: Disclosed herein is an object detection system, including apparatuses and methods for object detection. An implementation may include receiving a first image frame from an ROI detection model that generated a first ROI boundary around a first object detected in the first image frame and subsequently receiving a second image frame. The implementation further includes predicting, using an ROI tracking model, that the first ROI boundary will be present in the second image frame and then detecting whether the first ROI boundary is in fact present in the second image frame. The implementation includes determining that the second image frame should be added to a training dataset for the ROI detection model when detecting that the ROI detection model did not generate the first ROI boundary in the second image frame as predicted and re-training the ROI detection model using the training dataset.

Abstract: A building access system for a building including a front facing camera system configured to capture one or more images of a face of a user, wherein one or more front facing camera processing circuits configured to detect and authenticate the user based on the one or more images captured by the front facing camera system and operate building equipment. The system further including a down facing camera system configured to capture one or more overhead images of the user from an overhead perspective, wherein one or more down facing camera processing circuits configured to detect whether a second user is tailgating the user based on the one or more overhead images captured by the down facing camera system and generate an alarm in response to a detection that the second user is tailgating the user.

Abstract: A building radar-camera system includes a camera configured to capture one or images, the one or more images including first locations within the one or more images of one or more points on a world-plane and a radar system configured to capture radar data indicating second locations on the world-plane of the one or more points. The system includes one or more processing circuits configured to receive a correspondence between the first locations and the second locations of the one or more points, generate a sphere-to-plane homography, the sphere-to-plane homography translating between points captured by the camera modeled on a unit-sphere and the world-plane based on the correspondence between the first locations and the second locations, and translate one or more additional points captured by the camera or captured by the radar system between the unit-sphere and the world-plane based on the sphere-to-plane homography.

Abstract: A building radar-camera system includes a camera configured to capture one or images, the one or more images including first locations within the one or more images of one or more points on a world-plane and a radar system configured to capture radar data indicating second locations on the world-plane of the one or more points. The system includes one or more processing circuits configured to receive a correspondence between the first locations and the second locations of the one or more points, generate a sphere-to-plane homography, the sphere-to-plane homography translating between points captured by the camera modeled on a unit-sphere and the world-plane based on the correspondence between the first locations and the second locations, and translate one or more additional points captured by the camera or captured by the radar system between the unit-sphere and the world-plane based on the sphere-to-plane homography.

Abstract: A building radar-camera system includes a camera configured to capture one or images, the one or more images including first locations within the one or more images of one or more points on a world-plane and a radar system configured to capture radar data indicating second locations on the world-plane of the one or more points. The system includes one or more processing circuits configured to receive a correspondence between the first locations and the second locations of the one or more points, generate a sphere-to-plane homography, the sphere-to-plane homography translating between points captured by the camera modeled on a unit-sphere and the world-plane based on the correspondence between the first locations and the second locations, and translate one or more additional points captured by the camera or captured by the radar system between the unit-sphere and the world-plane based on the sphere-to-plane homography.

Abstract: A building access system for a building including a front facing camera system configured to capture one or more images of a face of a user, wherein one or more front facing camera processing circuits configured to detect and authenticate the user based on the one or more images captured by the front facing camera system and operate building equipment. The system further including a down facing camera system configured to capture one or more overhead images of the user from an overhead perspective, wherein one or more down facing camera processing circuits configured to detect whether a second user is tailgating the user based on the one or more overhead images captured by the down facing camera system and generate an alarm in response to a detection that the second user is tailgating the user.

Abstract: Systems and methods are provided for recognizing characters within a distorted image. According to a one aspect, a method for recognizing one or more characters within a distorted image includes rendering one or more imitation images, the imitation images including simulations of the distorted image, applying one or more distortion models to the imitation images, thereby generating distorted imitation images, comparing the distorted imitation images with the distorted image in order to compute similarities between the distorted imitation images and the distorted image, and identifying the characters based on the best similarity. According to other aspects, the systems and methods can be configured to provide recognition of other distorted data types and elements.

Abstract: Systems and methods are provided for recognizing characters within a distorted image. According to a one aspect, a method for recognizing one or more characters within a distorted image includes rendering one or more imitation images, the imitation images including simulations of the distorted image, applying one or more distortion models to the imitation images, thereby generating distorted imitation images, comparing the distorted imitation images with the distorted image in order to compute similarities between the distorted imitation images and the distorted image, and identifying the characters based on the best similarity. According to other aspects, the systems and methods can be configured to provide recognition of other distorted data types and elements.

Abstract: The present invention provides controllers, systems and methods that apply techniques for determining signal sequence characteristics that propagate through a sequence of buffers. One of the buffers represents buffering characteristics of a network through which the signal sequence propagates. The signal sequence may include packets of a media stream and the network may include a wireless network.

Abstract: The present invention provides controllers, systems and methods that apply techniques for determining signal sequence characteristics that propagate through a sequence of buffers. One of the buffers represents buffering characteristics of a network through which the signal sequence propagates. The signal sequence may include packets of a media stream and the network may include a wireless network.

Abstract: An apparatus and method for generating a motion compensated matrix, the method includes the steps of: (i) providing a motion vector and at least one input matrix of DCT coefficients; (ii) selecting at least one conversion transform (CT) and at least one inverse conversion transform (ICT) in response to a content of the motion vector; and (iii) applying the at least one selected ICT and the at least one selected CT to provide a motion compensated matrix.

Abstract: A method for transcoding a plurality of media items by allocation of processing power and storage through a combination of pre-processing the media item and processing in real time to provide transcoding of the plurality of media items. The method includes receiving information that relates to the computational and storage capabilities available for transcoding. The information received includes available power, available storage, variants to which to transcode and at least one of the respective probability and importance of the variants. The method also includes determining how to pre-process the plurality of media items in response to the received information, such that the transcoding is optimized.

Abstract: A method for streaming video in a varying bandwidth through scalable multi-level video coding, including: providing at least two compressed video streams, each stream including a respective plurality of Inter-frames; encoding at least one Inter-frame of each respective plurality at a respective quantization using an Intra-Block Refresh mechanism; creating at least one switch frame between any pair of the compressed video streams; and creating a mixed stream using any pair of compressed streams and the at least one switch frame.