Abstract: The present invention proposes a method and apparatus for correcting a motion of panorama video captured by a plurality of cameras. The method of the present invention includes performing global motion estimation for estimating smooth motion trajectories from the panorama video, performing global motion correction for correcting a motion in each frame of the estimated smooth motion trajectories, performing local motion correction for correcting a motion of each of the plurality of cameras for the results in which the motions have been corrected, and performing warping on the results on which the local motion correction has been performed.

Abstract: The input characteristics of a real-time IDS change continuously with time therefore setting a rigid (time and behavior invariant) classification threshold limits the accuracy that the IDS can potentially achieve. A generic threshold tuning method and system is proposed which can adaptively tune the detection threshold of a real-time IDS in accordance with varying host and network behavior. The method and system perform statistical and information-theoretic analysis of network and host-based IDSs' anomaly based intrusions to reveal a consistent time correlation structure between benign activity periods which is used to predict future anomaly scores and to adapt an IDS' detection threshold accordingly.

Abstract: Disclosed are a color correction apparatus for panorama video stitching and a method of selecting a reference image using the same. A method of selecting a reference image for color correction when stitching panorama video based on input images includes selecting an optimum reference image candidate from the input images based on standard deviations for overlapping regions between the input images, performing color correction on the input images based on the optimum reference image candidate, and validating the optimum reference image candidate based on the color-corrected input images.

Abstract: The input characteristics of a real-time IDS change continuously with time therefore setting a rigid (time and behavior invariant) classification threshold limits the accuracy that the IDS can potentially achieve. A generic threshold tuning method and system is proposed which can adaptively tune the detection threshold of a real-time IDS in accordance with varying host and network behavior. The method and system perform statistical and information-theoretic analyses of network and host-based IDSs' anomaly based intrusions to reveal a consistent time correlation structure between benign activity periods which is used to predict future anomaly scores and to adapt an IDS' detection threshold accordingly.