Abstract: An apparatus is provided for automated object tracking in a video feed. The apparatus receives and sequentially processes a plurality of frames of the video feed to track objects. In particular, a plurality of objects in a frame are detected and assigned to a respective track fragment. A kinematic, visual, temporal or machine learning-based feature of an object is then identified and stored in metadata associated with the track fragment. A track fragment for the object is identified in earlier frames based on a comparison of the feature and a corresponding feature in metadata associated with the earlier frames. The track fragments for the object in the frame and the object in the earlier frames are linked to form a track of the object. The apparatus then outputs the video feed with the track of the object as an overlay thereon.

Abstract: According to various embodiments, a technique for automated aircraft paint application quality inspection is presented. The technique includes retrieving from electronic persistent storage a control image depicting at least a portion of aircraft paint application for the aircraft under quality inspection; capturing a process image depicting at least a portion of aircraft paint application on the aircraft under quality inspection; detecting a plurality of features in the control image and the process image; registering the control image with the process image; detecting at least one difference between the control image and the process image; generating an output image, where the output image includes a depiction of the aircraft under quality inspection with the at least one difference annotated; and causing the output image to be displayed.

Abstract: According to various embodiments, a technique for automated aircraft paint application quality inspection is presented. The technique includes retrieving from electronic persistent storage a control image depicting at least a portion of aircraft paint application for the aircraft under quality inspection; capturing a process image depicting at least a portion of aircraft paint application on the aircraft under quality inspection; detecting a plurality of features in the control image and the process image; registering the control image with the process image; detecting at least one difference between the control image and the process image; generating an output image, where the output image includes a depiction of the aircraft under quality inspection with the at least one difference annotated; and causing the output image to be displayed.

Abstract: An apparatus is provided for automated object tracking in a video feed. The apparatus receives and sequentially processes a plurality of frames of the video feed to track objects. In particular, a plurality of objects in a frame are detected and assigned to a respective track fragment. A kinematic, visual, temporal or machine learning-based feature of an object is then identified and stored in metadata associated with the track fragment. A track fragment for the object is identified in earlier frames based on a comparison of the feature and a corresponding feature in metadata associated with the earlier frames. The track fragments for the object in the frame and the object in the earlier frames are linked to form a track of the object. The apparatus then outputs the video feed with the track of the object as an overlay thereon.

Abstract: A method and system for detecting floating objects in maritime video is disclosed. The horizon is detected within the video. Modeling of the sky and water is performed on the video. Objects are detected that are not water and sky within the video.

Abstract: A method and system for detecting floating objects in maritime video is disclosed. The horizon is detected within the video. Modeling of the sky and water is performed on the video. Objects are detected that are not water and sky within the video.