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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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The KIPS Transactions:PartB
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Korea Information Processing Society
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Volume & Issues
Volume 18B, Issue 6 - Dec 2011
Volume 18B, Issue 5 - Oct 2011
Volume 18B, Issue 4 - Aug 2011
Volume 18B, Issue 3 - Jun 2011
Volume 18B, Issue 2 - Apr 2011
Volume 18B, Issue 1 - Feb 2011
Selecting the target year
Performance Enhancement through Row-Column Cross Scanning in Differential Histogram-based Reversible Watermarking
Yeo, Dong-Gyu ; Lee, Hae-Yeoun ; Kim, Byeong-Man ;
The KIPS Transactions:PartB, volume 18B, issue 1, 2011, Pages 1~10
DOI : 10.3745/KIPSTB.2011.18B.1.001
Reversible watermarking inserts watermark into digital media in such a way that visual transparency is preserved, which enables the restoration of the original media from the watermarked one without any loss of media quality. It has various applications, where high capacity and high visual quality are major requirements. This paper presents a new effective multi-round embedding scheme for the differential histogram-based reversible watermarking that satisfies high capacity requirements of the application. The proposed technique exploits the row-column cross scanning to fully utilize the locality of images when multi-round embedding phase to the message inserted image. Through experiments using multiple kinds of test images, we prove that the presented algorithm provides 100% reversibility, effectiveness of multi-round embedding, and higher visual quality, while maintaining the induced-distortion low.
Key Pose-based Proposal Distribution for Upper Body Pose Tracking
Oh, Chi-Min ; Lee, Chil-Woo ;
The KIPS Transactions:PartB, volume 18B, issue 1, 2011, Pages 11~20
DOI : 10.3745/KIPSTB.2011.18B.1.011
Pictorial Structures is known as an effective method that recognizes and tracks human poses. In this paper, the upper body pose is also tracked by PS and a particle filter(PF). PF is one of dynamic programming methods. But Markov chain-based dynamic motion model which is used in dynamic programming methods such as PF, couldn't predict effectively the highly articulated upper body motions. Therefore PF often fails to track upper body pose. In this paper we propose the key pose-based proposal distribution for proper particle prediction based on the similarities between key poses and an upper body silhouette. In the experimental results we confirmed our 70.51% improved performance comparing with a conventional method.
A 3D Face Reconstruction and Tracking Method using the Estimated Depth Information
Ju, Myung-Ho ; Kang, Hang-Bong ;
The KIPS Transactions:PartB, volume 18B, issue 1, 2011, Pages 21~28
DOI : 10.3745/KIPSTB.2011.18B.1.021
A 3D face shape derived from 2D images may be useful in many applications, such as face recognition, face synthesis and human computer interaction. To do this, we develop a fast 3D Active Appearance Model (3D-AAM) method using depth estimation. The training images include specific 3D face poses which are extremely different from one another. The landmark's depth information of landmarks is estimated from the training image sequence by using the approximated Jacobian matrix. It is added at the test phase to deal with the 3D pose variations of the input face. Our experimental results show that the proposed method can efficiently fit the face shape, including the variations of facial expressions and 3D pose variations, better than the typical AAM, and can estimate accurate 3D face shape from images.
Effective Graph-Based Heuristics for Contingent Planning
Kim, Hyun-Sik ; Kim, In-Cheol ; Park, Young-Tack ;
The KIPS Transactions:PartB, volume 18B, issue 1, 2011, Pages 29~38
DOI : 10.3745/KIPSTB.2011.18B.1.029
In order to derive domain-independent heuristics from the specification of a planning problem, it is required to relax the given problem and then solve the relaxed one. In this paper, we present a new planning graph, Merged Planning Graph(MPG), and GD heuristics for solving contingent planning problems with both uncertainty about the initial state and non-deterministic action effects. The merged planning graph is an extended one to be applied to the contingent planning problems from the relaxed planning graph, which is a common means to get effective heuristics for solving the classical planning problems. In order to get heuristics for solving the contingent planning problems with sensing actions and non-deterministic actions, the new graph utilizes additionally the effect-merge relaxations of these actions as well as the traditional delete relaxations. Proceeding parallel to the forward expansion of the merged planning graph, the computation of GD heuristic excludes the unnecessary redundant cost from estimating the minimal reachability cost to achieve the overall set of goals by analyzing interdependencies among goals or subgoals. Therefore, GD heuristics have the advantage that they usually require less computation time than the overlap heuristics, but are more informative than the max and the additive heuristics. In this paper, we explain the experimental analysis to show the accuracy and the search efficiency of the GD heuristics.
A Design and Analysis of Improved Firefly Algorithm Based on the Heuristic
Rhee, Hyun-Sook ; Lee, Jung-Woo ; Oh, Kyung-Whan ;
The KIPS Transactions:PartB, volume 18B, issue 1, 2011, Pages 39~44
DOI : 10.3745/KIPSTB.2011.18B.1.039
In this paper, we propose a method to improve the Firefly Algorithm(FA) introduced by Xin-She Yang, recently. We design and analyze the improved firefly algorithm based on the heuristic. We compare the FA with the Particle Swarm Optimization (PSO) which the problem domain is similar with the FA in terms of accuracy, algorithm convergence time, the motion of each particle. The compare experiments show that the accuracy of FA is not worse than PSO's, but the convergence time of FA is slower than PSO's. In this paper, we consider intuitive reasons of slow convergence time problem of FA, and propose the improved version of FA using a partial mutation heuristic based on the consideration. The experiments using benchmark functions show the accuracy and convergence time of the improved FA are better than them of PSO and original FA.
Part-Of-Speech Tagging and the Recognition of the Korean Unknown-words Based on Machine Learning
Choi, Maeng-Sik ; Kim, Hark-Soo ;
The KIPS Transactions:PartB, volume 18B, issue 1, 2011, Pages 45~50
DOI : 10.3745/KIPSTB.2011.18B.1.045
Unknown morpheme errors in Korean morphological analysis are divided into two types: The one is the errors that a morphological analyzer entirely fails to return any morpheme sequences, and the other is the errors that a morphological analyzer returns incorrect combinations of known morphemes. Most previous unknown morpheme estimation techniques have been focused on only the former errors. This paper proposes a unknown morpheme estimation method which can handle both of the unknown morpheme errors. The proposed method detects Eojeols (Korean spacing units) that may include unknown morpheme errors using SVM (Support Vector Machine). Then, using CRFs (Conditional Random Fields), it segments morphemes from the detected Eojeols and annotates the segmented morphemes with new POS tags. In the experiments, the proposed method outperformed the conventional method based on the longest matching of functional words. Based on the experimental results, we knew that the second type errors should be dealt with in order to increase the performance of Korean morphological analysis.