Abstract: Video analytics data is audited through review of selective subsets of visual images from a visual image stream as a function of a temporal relationship of the images to a triggering alert event. The subset comprehends an image contemporaneous with the triggering alert event and one or more other images occurring before or after the contemporaneous image. The generated subset may be presented for review to determine whether the triggering alert event is a true or false alert, or whether additional data from the visual image stream is required to make such a determination. If determined from the presented visual essence that the additional data is required to make the true or false determination, then additional data is presented from the visual image stream for review.

Abstract: A computer identifies a proto-object in a digital image using a background subtraction method, the proto-object being associated with a lighting artifact in the surveillance region. The background subtraction method preserves boundary details and interior texture details of proto-objects associated with lighting artifacts. A plurality of characteristics of the proto-object digital data are determined, the characteristics, individually or in combination, distinguish a proto-object related to a lighting artifact from its background. A learning machine, trained with the plurality of characteristics of proto-objects classified as either foreground or not foreground, determines a likelihood that the plurality of characteristics is associated with a foreground object.

Abstract: Alerts to object behaviors are prioritized for adjudication as a function of relative values of abandonment, foregroundness and staticness attributes. The attributes are determined from feature data extracted from video frame image data. The abandonment attribute indicates a level of likelihood of abandonment of an object. The foregroundness attribute quantifies a level of separation of foreground image data of the object from a background model of the image scene. The staticness attribute quantifies a level of stability of dimensions of a bounding box of the object over time. Alerts are also prioritized according to an importance or relevance value that is learned and generated from the relative abandonment, foregroundness and staticness attribute strengths.

Abstract: Techniques for detecting one or more events are provided. The techniques include identifying one or more segments in a video sequence as one or more candidates for one or more events by a temporal ordering of the one or more candidates, and analyzing one or more motion patterns of the one or more candidates to detect the one or more events.

Abstract: Alerts to object behaviors are prioritized for adjudication as a function of relative values of abandonment, foregroundness and staticness attributes. The attributes are determined from feature data extracted from video frame image data. The abandonment attribute indicates a level of likelihood of abandonment of an object. The foregroundness attribute quantifies a level of separation of foreground image data of the object from a background model of the image scene. The staticness attribute quantifies a level of stability of dimensions of a bounding box of the object over time. Alerts are also prioritized according to an importance or relevance value that is learned and generated from the relative abandonment, foregroundness and staticness attribute strengths.

Abstract: Software for static object detection that performs the following operations: (i) detecting an object that is present in at least one image of a set of images, wherein the set of images correspond to a time period; (ii) identifying a set of corner points for the detected object; (iii) tracking the object's presence in the set of images over the time period, wherein the object's presence is determined by matching the set of images to a template generated based on the identified corner points; and (iv) identifying the object as a static object when an amount of time corresponding to the object's presence in the set of images is greater than a predefined threshold.

Abstract: Transaction units of video data and transaction data captured from different checkout lanes are prioritized as a function of lane priority values of respective ones of the different checkout lanes from which the transaction units are acquired. Each of the checkout lanes has a different lane priority value. The individual transaction units are processed in the prioritized processing order to automatically detect irregular activities indicated by the transaction unit video and the transaction data of the processed individual transaction units.

Abstract: Alerts to object behaviors are prioritized for adjudication as a function of relative values of abandonment, foregroundness and staticness attributes. The attributes are determined from feature data extracted from video frame image data. The abandonment attribute indicates a level of likelihood of abandonment of an object. The foregroundness attribute quantifies a level of separation of foreground image data of the object from a background model of the image scene. The staticness attribute quantifies a level of stability of dimensions of a bounding box of the object over time. Alerts are also prioritized according to an importance or relevance value that is learned and generated from the relative abandonment, foregroundness and staticness attribute strengths.

Abstract: Generating a composite geo-referenced panoramic field of view image of a geographic area is provided. Geodetic coordinates are generated for each of a plurality of pixels in a digital image capturing the geographic area based on a corrected amount of image distortion in each line of pixels in the plurality of pixels in the digital image. Each of the plurality of pixels in the digital image with the calculated geodetic coordinates is mapped to a geo-referenced map corresponding to the geographic area based on the calculated geodetic coordinates of each pixel. The composite geo-referenced panoramic field of view image of the geographic area is generated based on the mapping of each of the plurality of pixels in the digital image with the calculated geodetic coordinates to the geo-referenced map corresponding to the geographic area captured in the digital image.

Abstract: Transaction units of video data and transaction data captured from different checkout lanes are prioritized as a function of lane priority values of respective ones of the different checkout lanes from which the transaction units are acquired. Each of the checkout lanes has a different lane priority value. The individual transaction units are processed in the prioritized processing order to automatically detect irregular activities indicated by the transaction unit video and the transaction data of the processed individual transaction units.

Abstract: Generating a composite geo-referenced panoramic field of view image of a geographic area is provided. Geodetic coordinates are generated for each of a plurality of pixels in a digital image capturing the geographic area based on a corrected amount of image distortion in each line of pixels in the plurality of pixels in the digital image. Each of the plurality of pixels in the digital image with the calculated geodetic coordinates is mapped to a geo-referenced map corresponding to the geographic area based on the calculated geodetic coordinates of each pixel. The composite geo-referenced panoramic field of view image of the geographic area is generated based on the mapping of each of the plurality of pixels in the digital image with the calculated geodetic coordinates to the geo-referenced map corresponding to the geographic area captured in the digital image.

Abstract: A method for summarizing image content from video images received from a moving camera includes detecting foreground objects in the images, determining moving objects of interest from the foreground objects, tracking the moving objects, rating movements of the tracked objects, and generating a list of highly rated segments within the video images based on the ratings.

Abstract: A method for summarizing image content from video images received from a moving camera includes detecting foreground objects in the images, determining moving objects of interest from the foreground objects, tracking the moving objects, rating movements of the tracked objects, and generating a list of highly rated segments within the video images based on the ratings.

Abstract: Alerts to object behaviors are prioritized for adjudication as a function of relative values of abandonment, foregroundness and staticness attributes. The attributes are determined from feature data extracted from video frame image data. The abandonment attribute indicates a level of likelihood of abandonment of an object. The foregroundness attribute quantifies a level of separation of foreground image data of the object from a background model of the image scene. The staticness attribute quantifies a level of stability of dimensions of a bounding box of the object over time. Alerts are also prioritized according to an importance or relevance value that is learned and generated from the relative abandonment, foregroundness and staticness attribute strengths.

Abstract: Alerts to object behaviors are prioritized for adjudication as a function of relative values of abandonment, foregroundness and staticness attributes. The attributes are determined from feature data extracted from video frame image data. The abandonment attribute indicates a level of likelihood of abandonment of an object. The foregroundness attribute quantifies a level of separation of foreground image data of the object from a background model of the image scene. The staticness attribute quantifies a level of stability of dimensions of a bounding box of the object over time. Alerts are also prioritized according to an importance or relevance value that is learned and generated from the relative abandonment, foregroundness and staticness attribute strengths.

Abstract: Video analytics data is audited through review of selective subsets of visual images from a visual image stream as a function of a temporal relationship of the images to a triggering alert event. The subset comprehends an image contemporaneous with the triggering alert event and one or more other images occurring before or after the contemporaneous image. The generated subset may be presented for review to determine whether the triggering alert event is a true or false alert, or whether additional data from the visual image stream is required to make such a determination. If determined from the presented visual essence that the additional data is required make the true or false determination, then additional data is presented from the visual image stream for review.

Abstract: Generating a composite geo-referenced panoramic field of view image of a geographic area is provided. Geodetic coordinates are generated for each of a plurality of pixels in a digital image capturing the geographic area based on a corrected amount of image distortion in each line of pixels in the plurality of pixels in the digital image. Each of the plurality of pixels in the digital image with the calculated geodetic coordinates is mapped to a geo-referenced map corresponding to the geographic area based on the calculated geodetic coordinates of each pixel. The composite geo-referenced panoramic field of view image of the geographic area is generated based on the mapping of each of the plurality of pixels in the digital image with the calculated geodetic coordinates to the geo-referenced map corresponding to the geographic area captured in the digital image.

Abstract: Generating a composite geo-referenced panoramic field of view image of a geographic area is provided. Geodetic coordinates are generated for each of a plurality of pixels in a digital image capturing the geographic area based on a corrected amount of image distortion in each line of pixels in the plurality of pixels in the digital image. Each of the plurality of pixels in the digital image with the calculated geodetic coordinates is mapped to a geo-referenced map corresponding to the geographic area based on the calculated geodetic coordinates of each pixel. The composite geo-referenced panoramic field of view image of the geographic area is generated based on the mapping of each of the plurality of pixels in the digital image with the calculated geodetic coordinates to the geo-referenced map corresponding to the geographic area captured in the digital image.

Abstract: Video analytics data is audited through review of selective subsets of visual images from a visual image stream as a function of a temporal relationship of the images to a triggering alert event. The subset comprehends an image contemporaneous with the triggering alert event and one or more other images occurring before or after the contemporaneous image. The generated subset may be presented for review to determine whether the triggering alert event is a true or false alert, or whether additional data from the visual image stream is required to make such a determination. If determined from the presented visual essence that the additional data is required make the true or false determination, then additional data is presented from the visual image stream for review.

Abstract: A method for summarizing image content from video images received from a moving camera includes detecting foreground objects in the images, determining moving objects of interest from the foreground objects, tracking the moving objects, rating movements of the tracked objects, and generating a list of highly rated segments within the video images based on the ratings.