Abstract: A surveillance camera includes a slip ring having electrical connections for Ethernet protocol signals and a RF reference plane. A first circuit is located on a rotating portion of the surveillance camera and electrically connected to the camera for compressing signals generated by the camera and for converting the signals generated by the camera to Ethernet protocol signals. The slip ring has a stationary portion and a rotating portion, each with a corresponding plurality of electrical connection. An RF reference plane is located on the stationary portion of the surveillance camera and electrically connected to a first subset of the plurality of electrical connections of the stationary portion of the slip ring. A second subset of the plurality of electrical connections of the stationary portion of the slip ring conducts the Ethernet protocol signals and is arranged in alternation with each electrical connection of said first subset.

Abstract: Disclosed are methods, systems, computer readable media and other implementations, including a method to calibrate a camera that includes capturing by the camera a frame of a scene, identifying features appearing in the captured frame, the features associated with pre-determined values representative of physical attributes of one or more objects, and determining parameters of the camera based on the identified features appearing in the captured frame and the pre-determined values associated with the identified features.

Abstract: Techniques are discussed herein for providing mechanisms for coding and transmitting high definition video, e.g., over low bandwidth connections. In particular, foreground-objects are identified as distinct from the background of a scene represented by a plurality of video frames. In identifying foreground-objects, semantically significant and semantically insignificant movement (e.g., non-repetitive versus repetitive movement) is differentiated. For example, the swaying motion of a tree's leaves being minor and repetitive, can be determined to be semantically insignificant and to belong in a scene's background. Processing of the foreground-objects and background proceed at different update rates or frequencies. For example, foreground-objects can be updated 30 or 60 times per second. By contrast, a background is updated less frequently, e.g., once every 10 seconds. In some implementations, if no foreground-objects are identified, no live video is transmitted (e.g.

Abstract: An example of a method for identifying objects in video content according to the disclosure includes receiving video content of a scene captured by a video camera, detecting an object in the video content, identifying a track that the object follows over a series of frames of the video content, extracting object features for the object from the video content, and classifying the object based on the object features. Classifying the object further comprises: determining a track-level classification for the object using spatially invariant object features, determining a global-clustering classification for the object using spatially variant features, and determining an object type for the object based on the track-level classification and the global-clustering classification for the object.

Abstract: An example method for processing visual communications at a video camera according to the disclosure includes analyzing video content captured by the video camera to identify a visual command presented to the camera by a user in the field of view of the camera, executing the visual command identified from the video content captured by the video camera, wherein executing the visual command includes setting one or more operating parameters of the video camera, determining a command completion indication corresponding to whether the command was successfully executed, and providing a command completion indication, corresponding to the command completion indication, to the user.

Abstract: A method of presenting video comprising receiving a plurality of video data from a video source, analyzing the plurality of video data; identifying the presence of foreground-objects that are distinct from background portions in the plurality of video data, classifying the foreground-objects into foreground-object classifications, receiving user input selecting a foreground-object classification, and generating video frames from the plurality of video data containing background portions and only foreground-objects in the selected foreground-object classification.

Abstract: Techniques for processing video content in a video camera are provided. The techniques include a method for processing video content in at video camera according to the disclosure includes capturing thermal video data using a thermal imaging sensor, determining quantization parameters for the thermal video data, quantizing the thermal video data to generate quantized thermal video data content and video quantization information, and transmitting the quantized thermal video data stream and the video quantization information to a video analytics server over a network.

Abstract: A method of displaying a timeline of recorded video comprising the steps of dividing the recorded video into timespans, providing a thumbnail and a timestamp for each timespan that has recorded video, providing a gap and a timestamp between thumbnails for each timespan in which there is no recorded video, displaying a first timeline containing the provided thumbnails and timestamps and the provided gaps and timestamps having an uncompressed format, receiving user input requesting that the first timeline be compressed, removing the gaps and their respective timestamps from the first timeline and moving the thumbnails and their timestamps located on either side of the gaps so that the thumbnails on either side of the gaps are adjacent to provide a compressed timeline, and displaying the compressed timeline.

Abstract: Systems and methods for transformations between image and map coordinates, such as those associated with a video surveillance system, are described herein. An example of a method described herein includes selecting a reference point within the image with known image coordinates and map coordinates, computing at least one transformation parameter with respect to a location and a height of the camera and the reference point, detecting a target location to be tracked within the image, determining image coordinates of the target location, and computing map coordinates of the target location based on the image coordinates of the target location and the at least one transformation parameter.

Abstract: Systems and methods are described for determining device positions in a video surveillance system. A method described herein includes generating a reference sound; emitting, at a first device, the reference sound; detecting, at the first device, a responsive reference sound from one or more second devices in response to the emitted reference sound; identifying a position of each of the one or more second devices; obtaining information relating to latency of the one or more second devices; computing a round trip time associated with each of the one or more second devices based on at least a timing of detecting the one or more responsive reference sounds and the latency of each of the one or more second devices; and estimating the position of the first device according to the round trip time and the position associated with each of the one or more second devices.

Abstract: Systems and methods are described herein that provide a three-tier intelligent video surveillance management system. An example of a system described herein includes a gateway configured to obtain video content and metadata relating to the video content from a plurality of network devices, a metadata processing module communicatively coupled to the gateway and configured to filter the metadata according to one or more criteria to obtain a filtered set of metadata, a video processing module communicatively coupled to the gateway and the metadata processing module and configured to isolate video portions, of video the content, associated with respective first portions of the filtered set of metadata, and a cloud services interface communicatively coupled to the gateway, the metadata processing module and the video processing module and configured to provide at least some of the filtered set of metadata or the isolated video portions to a cloud computing service.

Abstract: A method of adjusting the color of images captured by a plurality of cameras comprises the steps of receiving a first image captured by a first camera from the plurality of cameras, analyzing the first image to separate the pixels in the first image into background pixels and foreground pixels, selecting pixels from the background pixels that have a color that is a shade of gray, determining the amount to adjust the colors of the selected pixels to move their colors towards true gray, and providing information for use in adjusting the color components of images from the plurality of cameras.

Abstract: The methods and systems described herein are directed to image processing. More specifically, the image processing described herein may include centering an object in the field of view during zooming. The image processing methods and systems may further include setting a magnification factor, positioning the camera in a first field of view capturing a first image, setting a second magnification factor, and capturing a second image. Additionally, the described techniques may include altering the first image to determine an offset and adjusting the camera based on the offset.

Abstract: Embodiments of the disclosure provide for systems and methods for creating metadata associated with a video data. The metadata can include data about objects viewed within a video scene and/or events that occur within the video scene. Some embodiments allow users to search for specific objects and/or events by searching the recorded metadata. In some embodiments, metadata is created by receiving a video frame and developing a background model for the video frame. Foreground object(s) can then be identified in the video frame using the background model. Once these objects are identified they can be classified and/or an event associated with the foreground object may be detected. The event and the classification of the foreground object can then be recorded as metadata.

Abstract: An apparatus for and method of storing video data comprising receiving an MPEG video stream comprising I-frames and P-frames, separating the I-frames from the P-frames, storing the I-frames and the P-frames separately, and providing information so that the I-frames and the P-frames can be combined to produce a full-motion video.

Abstract: A method of and apparatus for allowing a user to access an electronic device by entering a password from a first device having alphabetic letter keys and numerical digit keys and a second device having primarily numerical digit keys comprising creating an alphabetic letter conversion relationship between the alphabetic letter keys of the first device with the numerical digit keys of the second device, creating a numerical digit conversion relationship between the numerical digit keys of the first device with the numerical digit keys of the second device, receiving a first password entered from the first device having alphabetic letter keys and numerical digit keys, converting the first password to a second password that can be entered from the second device having primarily numerical digit keys by using the alphabetic letter conversion relationship and the numerical digit conversion relationship, and allowing a user to access the electronic device if the user enters the first password or the second password.

Abstract: The invention relates to a system and method for monitoring connection performance within a network. In one embodiment, the invention is implemented by analyzing an array of status bits outputted by an analog to digital video decoder. By storing and statistically analyzing an array of status information units, the person monitoring the network can quickly and efficiently be notified of a connection problem, such as a degrading connection resulting in an intermittent signal. In another embodiment, the system and method are implemented by analyzing an array of time stamps outputted when processing frames of video from an analog video camera.

Abstract: A method of improving a video image by removing the effects of camera vibration comprising the steps of, obtaining a reference frame, receiving an incoming frame, determining the frame translation vector for the incoming frame, translating the incoming frame to generate a realigned frame, performing low pass filtering in the spatial domain on pixels in the realigned frame, performing low pass filtering in the spatial domain on pixels in the reference frame, determining the absolute difference between the filtered pixels in the reference frame and the filtered pixels in the realigned frame, performing low pass filtering in the temporal domain on the pixels in the realigned frame to generate the output frame if the absolute difference is less than a predetermined threshold, and providing the realigned frame as the output frame if the absolute difference is greater than the predetermined threshold.

Abstract: Techniques are discussed for providing mechanisms for coding and transmitting high definition video, e.g., over low bandwidth connections. In particular, foreground-objects are identified as distinct from the background of a scene represented in a plurality of video frames received from a video source, such as a camera. In identifying foreground-objects, semantically significant and semantically insignificant movement (e.g., repetitive versus non-repetitive movement) is differentiated. Processing of the foreground-objects and background proceed at different update rates or frequencies.

Abstract: Systems and methods of sorting electronic color images of objects are provided. One method includes receiving an input representation of an object, the representation including pixels defined in a first color space, converting the input image into a second color space, determining a query feature vector including multiple parameters associated with color of the input representation, the query feature vector parameters including at least a first parameter of the first color space and at least a first parameter of the second color space and comparing the query feature vector to multiple candidate feature vectors. Each candidate feature vector includes multiple parameters associated with color of multiple stored candidate images, the candidate feature vector parameters including at least the first parameter from the first color space and at least the first parameter from the second color space.