Woonkyung Michael Kim

Processing of partial video data for detection of wipes

With the currently existing shot change detection algorithms, abrupt changes are detected fairly well. It is thus more challenging to detect gradual changes, including fades, dissolves, and wipes, as these are often missed or falsely detected. In this paper, we focus on the detection of wipes. The proposed algorithm begins by processing the visual rhythm, a portion of the DC image sequence. It is a single image, a sub-sampled version of a full video, in which the sampling is performed in a predetermined and systematic fashion. The visual rhythm contains distinctive patterns or visual features for many different types of video effects. The different video effects manifest themselves differently on the visual rhythm. In particular, wipes appear as curves, which run from the top to the bottom of the visual rhythm. Thus, using the visual rhythm, it becomes possible to automatically detect wipes, simply by determining various lines and curves on the visual rhythm.

A numerical study on dynamic characteristics of a catenary

Dynamic characteristics of a catenary that supplies electrical power to high-speed railway is investigated. The catenary is a slender structure composed of repeating spans. Each span is in turn composed of the contact and messenger wires connected by the hangers in regular intervals. A finite element based dynamic model is developed, and numerical simulations are performed to determine the dynamic characteristics of the catenary. The influence of the structural parameters on the response characteristics is investigated. The structural parameters considered include tension on the contact and messenger wires, stiffness of the hangers, and the hanger and span spacing. The hanger characteristics are found to be the dominant factors that influence the overall dynamic characteristics of the catenary.

Visual Rhythm and Shot Verification

Typical result of an automatic shot change detection algorithm expectedly includes a certain number of undetected shots as well as falsely detected shots. Even though automatic shot change detection algorithms are continuing to improve, the ultimate goal of automatically detecting all shot changes without false alarms may never be achieved. Thus, allowing a human operator to intervene—to review and verify the result of a shot change detection algorithm, to delete falsely detected shots as well as to find undetected shots—may be the most viable approach currently available for increasing the accuracy of the overall shot detection process. For this exact purpose, we propose a shot verifier based on the visual rhythm.The visual rhythm, an abstraction of the video, is a single image, a sub-sampled version of a full video in which the sampling is performed in a pre-determined and in a systematic fashion. It is a representation of the video, which includes the overall content of the video. But most importantly, the visual rhythm contains patterns or visual features that allow the viewer/operator to distinguish and classify many different types of video effects (edits and otherwise): cuts, wipes, dissolves, fades, camera motions, object motions, flashlights, zooms, etc. The different video effects manifest themselves as different patterns on the visual rhythm. Using the visual rhythm, it becomes possible, without sequentially playing the entire video, to find false positive shots as well as undetected shots. Thus, inclusion of the visual rhythm in the shot verification process will aid the operator to verify detected shots as well as to find undetected shots fast and efficiently.Our newly developed shot verifier based on the visual rhythm has been designed for operator efficiency. The design of our shot verifier presented and the usefulness of the visual rhythm during the shot verification process will be demonstrated.

Development of a criterion for efficient numerical calculation of structural vibration responses

The finite element method is one of the methods widely applied for predicting vibration in mechanical structures. In this paper, the effect of the mesh size of the finite element model on the accuracy of the numerical solutions of the structural vibration problems is investigated with particular focus on obtaining the optimal mesh size with respect to the solution accuracy and computational cost. The vibration response parameters of the natural frequency, modal density, and driving point mobility are discussed. For accurate driving point mobility calculation, the decay method is employed to experimentally determine the internal damping. A uniform plate simply supported at four corners is examined in detail, in which the response parameters are calculated by constructing finite element models with different mesh sizes. The accuracy of the finite element solutions of these parameters is evaluated by comparing with the analytical results as well as estimations based on the statistical energy analysis, or if not available, by testing the numerical convergence. As the mesh size becomes smaller than one quarter of the wavelength of the highest frequency of interest, the solution accuracy improvement is found to be negligible, while the computational cost rapidly increases. For mechanical structures, the finite element analysis with the mesh size of the order of quarter wavelength, combined with the use of the decay method for obtaining internal damping, is found to provide satisfactory predictions for vibration responses.

Fast algorithm for detection of camera motion

Most image analysis/understanding applications require accurate computation of camera motion parameters. However, in multimedia applications, particularly in video parsing, the exact camera motion parameters such as the panning and/or zooming rates are not needed. The detection--i.e., a binary decision--of camera motion is all that is required to avoid declaring a false scene change. As camera motions can induce false scene changes for video parsing algorithms, we propose a fast algorithm to detect such camera motions: camera zoom and pan. As the algorithm is only expected produce a binary decision, without the exact panning/zooming rates, the proposed algorithm runs on a reduced data set, namely the projection data. The algorithm begins with a central portion of the image and computes the projection data (or the line integrals along the x- or y-axis) to turn the 2D image data into a 1D data. This projected 1D data is further processed via correlation processing to detect camera zoom and pan. Working with projection data saves processing time by an order of magnitude, since for instance, a 2D correlation takes N2 multiplies per point, however a 1D correlation takes N multiplies per point. The efficacy of the proposed algorithm is tested for a number of image sequences and the algorithm is shown to be successful in detecting camera motions. The proposed algorithm is expected to be beneficial for video parsers working with Motion-JPEG data stream where motion vectors are not available.

Morphological approach to scene change detection and digital video storage and retrieval

With the abstraction of digital video, as the corresponding binary video, a process which, upon subjective experimentation seems to preserve the intelligibility of video content, we can pursue a precise and analytic approach to digital video storage and retrieval algorithm design based upon geometrical and morphological intuition. The foremost and tangible general benefit of such abstraction, however, is the immediate reduction of both data and computational complexities, involved in implementing various algorithms and databases. The general paradigm presented may be utilized to address all issues pertaining to video library construction, including visualization, optimum feedback query generation, and object recognition. However, the primary focus of attention in this paper pertains to detection of fast and gradual scene changes, such as dissolves, fades, and various special effects, such as wipes. Upon simulation, we observed that we can achieve performances comparable to those of others with drastic reductions in both storage and computational complexities. The conversion from grayscale to binary videos can be performed directly (with minimal additional computation) in the compressed domain by thresholding on the DCT DC coefficients themselves, or by using the contour information attached to MPEG4 formats. The algorithms presented herein are ideally suited for performing fast (on-the-fly) determinations of scene change, object recognition, and/or tracking, as well as other, more intelligent, tasks, traditionally requiring heavy demand of computational and/or storage complexities. The fast determinations may then be used on their own merit , or can be used in conjunction/complement with other higher-layer information in the future.

Morphological approach to smoothing: stochastic morphological sampling theorem

From Communication to Pattern Recognition, from low layer signal processing to high layer cognition, from practice to theory of engineering principles, the question of inherent complexities of entities represented as sets in euclidean space is of fundamental interest. In this paper, we present some fundamental theoretical results pertaining to the question of how many randomly selected labelled example points it takes to reconstruct a set in euclidean space, and thereby propose a morphological sampling theorem in the form of Stochastic Morphological Sampling Theorem. Drawing on results and concepts from Mathematical Morphology and Learnability Theory, we pursue a set-theoretic approach and demonstrate some provable performances pertaining to euclidean-set- reconstruction from stochastic samples. In particular, we demonstrate a result towards the formulation of a stochastic (morphological) version of the Nyquist Sampling Theorem -- that, under weak assumptions on the situation under consideration, the number of randomly-drawn (positive) example points needed to reconstruct the target set is at most polynomial in the performance parameters and also the complexity of the target set as loosely captured by size, dimension and surface-area. The reconstruction result of this paper pertaining to the complexity of euclidean sets has natural interpretations for the process of smoothing modelled formally as a dilation and morphological operation. Thus, in this paper, we formulate and demonstrate a certain fundamental (distribution-free) well-behaving aspect of smoothing by proving a fundamental result pertaining to the (set-theoretic) complexity of sets in euclidean space.

Morphological approach to smoothing

In this paper, we present some fundamental theoretical results pertaining to the question of how many randomly selected labelled example points it takes to reconstruct a set in euclidean space. Drawing on results and concepts from mathematical morphology and learnability theory, we pursue a set-theoretic approach and demonstrate some provable performances pertaining to euclidean-set-reconstruction from stochastic samples. In particular, we demonstrate a stochastic version of the Nyquist Sampling Theorem - that, under weak assumptions on the situation under consideration, the number of randomly-drawn example points needed to reconstruct the target set is at most polynomial in the performance parameters and also the complexity of the target set as loosely captured by size, dimension and surface-area. Utilizing only rigorous techniques, we can similarly establish many significant attributes - such as those relating to robustness, cumulativeness and ease-of- implementation - pertaining to smoothing over labelled example points. In this paper, we formulate and demonstrate a certain fundamental well-behaving aspect of smoothing.

Optimization of radar pulse compression processing

We propose an optimal radar pulse compression technique and evaluate its performance in the presence of Doppler shift. The traditional pulse compression using Barker code increases the signal strength by transmitting a Barker coded long pulse. The received signal is then processed by an appropriate correlation processing. This Barker code radar pulse compression enhances the detection sensitivity while maintaining the range resolution of a single chip of the Barker coded long pulse. But unfortunately, the technique suffers from the addition of range sidelobes which sometimes will mask weak targets in the vicinity of larger targets. Our proposed optimal algorithm completely eliminates the sidelobes at the cost of additional processing.