Wavelet based Keyframe Extraction Method from Motion Capture Data
نویسندگان
چکیده
This research extracts keyframes from Motion capture data. Accurate selection of keyframes is a key point in motion synthesizing, editing, retargeting and motion data compression. Our method firstly represents every joint curve with a simple numeric sequence based on wavelet transformation. Then the correlation between curves is calculated based on these numeric sequences. Several curves which are least correlated are chosen for keyframe extraction. In the next step, a noise filter is applied to selected curves. Finally the keyframes are selected from the de-noised curves. Keyword: Animation, Motion capture data, Keyframe extraction
منابع مشابه
An Efficient Keyframe Extraction from Motion Capture Data
This paper proposes a keyframe extraction method based on a novel layered curve simplification algorithm for motion capture data. Bone angles are employed as motion features and keyframe candidates can be selected based on them. After that, the layered curve simplification algorithm will be used to refine those candidates and the keyframe collection can be gained. To meet different requirements...
متن کاملKeyframe Extraction from Human Motion Capture Data Based on a Multiple Population Genetic Algorithm
To reduce reconstruction errors during keyframe extraction and to control the optimal compression ratio, this study proposes a method for keyframe extraction from human motion capture data based on a multiple population genetic algorithm. The fitness function is defined to meet the goals of minimal reconstruction errors and the optimal compression rate, where multiple initial populations are su...
متن کاملHuman Gait Gender Classification using 3D Discrete Wavelet Transform Feature Extraction
Feature extraction for gait recognition has been created widely. The ancestor for this task is divided into two parts, model based and free-model based. Model-based approaches obtain a set of static or dynamic skeleton parameters via modeling or tracking body components such as limbs, legs, arms and thighs. Model-free approaches focus on shapes of silhouettes or the entire movement of physical ...
متن کاملMultiscale motion saliency for keyframe extraction from motion capture sequences
Motion capture is an increasingly popular animation technique; however data acquired by motion capture can become substantial. This makes it difficult to use motion capture data in a number of applications, such as motion editing, motion understanding, automatic motion summarization, motion thumbnail generation, or motion database search and retrieval. To overcome this limitation, we propose an...
متن کاملWavelet-based feature extraction using probabilistic finite state automata for pattern classification
Real-time data-driven pattern classification requires extraction of relevant features from the observed time series as low-dimensional and yet information-rich representations of the underlying dynamics. These low-dimensional features facilitate in situ decision-making in diverse applications, such as computer vision, structural health monitoring, and robotics. Wavelet transforms of time series...
متن کامل