Classification and translation of style and affect in human motion using RBF neural networks

Etemad, S. Ali; Arya, Ali

doi:10.1016/j.neucom.2013.09.001

Cited by 45 publications

(31 citation statements)

References 38 publications

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“…Eq. (6) indicates that to acquire minimum SNR −1 , D in,CoT W must approach D in . As a result, minimizing this measurement during the warping process tends to cancel out the attempts made to carry out the non-uniform segment-wise warps.…”

Section: Parameters and Distortionmentioning

confidence: 99%

“…For example, we used first and second derivatives of the components in Eq. (6). We also experimented with using the difference of the norms instead of the norm of differences.…”

Section: Parameters and Distortionmentioning

confidence: 99%

“…On the other hand, in many cases, processing human motion requires motion data to be perfectly aligned. For example, it has been demonstrated that altering [3], blending [4], extraction [5], and translation [6] of style features require aligned motion data.…”

Section: Introductionmentioning

confidence: 99%

“…The method proposed in this paper is inspired by correlation-optimized warping, which was initially developed for aligning chemometric data [10]. We briefly introduced the concept in [11] and utilized it in [5,6,12]. In this paper, we further develop the technique, study the parameters involved, and take a deep look into its performance, especially with respect to existing timewarping methods.…”

Section: Introductionmentioning

confidence: 99%

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Correlation-optimized time warping for motion

Etemad

Arya

2014

Vis Comput

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Retrieval and comparative editing/modeling of motion data require temporal alignment. In other words, for such processes to perform accurately, critical features of motion sequences need to occur simultaneously. In this paper, we propose correlation-optimized time warping (CoTW) for aligning motion data. CoTW utilizes a correlation-based objective function for characterizing alignment. The method solves an optimization problem to determine the optimum warping degree for different segments of the sequence. Using segment-wise interpolated warping, smooth motion trajectories are achieved that can be readily used for animation. Our method allows for manual tuning of the parameters, resulting in high customizability with respect to the number of actions in a single sequence as well as spatial regions of interest within the character model. Moreover, measures are taken to reduce distortion caused by over-warping. The framework also allows for automatic selection of an optimum reference when multiple sequences are available. Experimental results demonstrate the very accurate performance of CoTW compared to other techniques such as dynamic time warping, derivative dynamic time warping and canonical time warping. The mentioned customization capabilities are also illustrated. Electronic supplementary materialThe online version of this article (

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Section: Parameters and Distortionmentioning

confidence: 99%

“…For example, we used first and second derivatives of the components in Eq. (6). We also experimented with using the difference of the norms instead of the norm of differences.…”

Section: Parameters and Distortionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Correlation-optimized time warping for motion

Etemad

Arya

2014

Vis Comput

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“…An ensemble model is a multiclassifier combination model that results in more precise decisions because the same problem is solved by several different trained classifiers, which reduces the variance of error estimation [43]. In recent years, ensemble learning has been employed to increase classification accuracies beyond the level that can be achieved by individual classifiers [44, 45]. In this paper, we used an ensemble classifier to evaluate the feature selection model.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Classification System for Heart Disease Diagnosis Based on the RFRS Method

Liu

Wang

et al. 2017

Computational and Mathematical Methods in Medicine

123

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Heart disease is one of the most common diseases in the world. The objective of this study is to aid the diagnosis of heart disease using a hybrid classification system based on the ReliefF and Rough Set (RFRS) method. The proposed system contains two subsystems: the RFRS feature selection system and a classification system with an ensemble classifier. The first system includes three stages: (i) data discretization, (ii) feature extraction using the ReliefF algorithm, and (iii) feature reduction using the heuristic Rough Set reduction algorithm that we developed. In the second system, an ensemble classifier is proposed based on the C4.5 classifier. The Statlog (Heart) dataset, obtained from the UCI database, was used for experiments. A maximum classification accuracy of 92.59% was achieved according to a jackknife cross-validation scheme. The results demonstrate that the performance of the proposed system is superior to the performances of previously reported classification techniques.

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Perceptual validity in animation of human motion

Etemad

Arya

Parush

et al. 2015

Computer Animation & Virtual

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The crucial concept of modeling and synthesis/control of human motion (including face and body) for animation has been widely studied and explored in the literature. In this regard, the audience's perception of generated or recorded animation scenes is of critical importance. In this paper, we explore and conceptualize the general notions that need to be taken into account for human motion to maintain perceptual accuracy. We propose a paradigm called Perceptual Validity composed of four major components, which are discussed in detail. The model is concerned with different aspects of the scene such as correct illustration of the stimuli, context, and local/global relations of various visual cues present in human motion. Satisfying all the proposed principles, based on the literature, seems compulsory and vital for synthesis of perceptually valid animation scenes of human motion. We investigate the relative significance of the different components of the paradigm using feedback from expert animators and conduct a case study on one of the components of the paradigm. For further evaluation and exploration, Disney's principles of animation are discussed and compared against our proposed paradigm. We argue that while there are significant parallels and overlaps, our model is only focused on and more inclusive towards human motion and can therefore provide a valuable set of guidelines for animators in the field of character animation. Copyright © 2015 John Wiley & Sons, Ltd.

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Classification and translation of style and affect in human motion using RBF neural networks

Cited by 45 publications

References 38 publications

Correlation-optimized time warping for motion

Correlation-optimized time warping for motion

A Hybrid Classification System for Heart Disease Diagnosis Based on the RFRS Method

Perceptual validity in animation of human motion

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