Motion Key-frames extraction based on amplitude of distance characteristic curve
نویسندگان
چکیده
The key frames extraction technique extracts key postures to describe the original motion sequence, which has been widely used in motion compression, motion retrieval, motion edition and so on. In this paper, we propose a method based on the amplitude of curve to find key frames in a motion captured sequence. First we select a group of joint distance features to represent the motion and adopt the Principal Component Analysis (PCA) method to obtain the one dimension principal component as a features curve which will be used. Then we gain the initial key-frames by extracting the local optimum points in the curve. At last, we get the final key frames by inserting frames based on the amplitude of the curve and merging key frames too close. A number of experimental examples demonstrate that our method is practicable and efficient not only in the visual performance but also in the aspect of the compression ratio and error rate.
منابع مشابه
Single station estimation of earthquake early warning parameters by using amplitude envelope curve
In this study, new empirical relationships to estimate key parameters in Earthquake Early Warning (EEW) system including magnitude, epicentral distance and Peak Ground Acceleration (PGA) are introduced based on features of the initial portion of P-wave’s amplitude envelope curve. For this purpose, 226 time series recorded by bore-hole accelerometers of Japanese KiK-net are processed for earthq...
متن کاملKey Frame Extraction from Motion Capture Data by Curve Saliency
We propose a new method for extracting key frames from a motion capture sequence. Our proposed approach consists of two steps. In the first step, we propose a new metric, curve saliency, for motion curves that specifies the important frames of the motion. In the second step, we detect the final key frames by clustering the computed important frames. As a result of our experimental results, on t...
متن کاملAn Efficient Method of Key-Frame Extraction Based on a Cluster Algorithm
This paper proposes a novel method of key-frame extraction for use with motion capture data. This method is based on an unsupervised cluster algorithm. First, the motion sequence is clustered into two classes by the similarity distance of the adjacent frames so that the thresholds needed in the next step can be determined adaptively. Second, a dynamic cluster algorithm called ISODATA is used to...
متن کاملUnsupervised Clustering by k-medoids for Video Summarization
In this paper, we propose a video summarization algorithm by multiple extractions of key frames in each shot. This algorithm is based on the k partition algorithms. We choose the ones based on k-medoid clustering methods so as to find the best representative object for each partitions. In order to find the number of partition (i.e. the number of representative frames of each shot), we introduce...
متن کاملRemoving car shadows in video images using entropy and Euclidean distance features
Detecting car motion in video frames is one of the key subjects in computer vision society. In recent years, different approaches have been proposed to address this issue. One of the main challenges of developed image processing systems for car detection is their shadows. Car shadows change the appearance of them in a way that they might seem stitched to other neighboring cars. This study aims ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Int. J. Computational Intelligence Systems
دوره 7 شماره
صفحات -
تاریخ انتشار 2014