The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
We are developing an appearance-based proficiency evaluation system for individual fundamental football skills. As a basic stage of the research, we propose a method to discriminate between beginners and experts based on features of the inside-kick motion, which is a fundamental skill in football. In addition, we propose a method for scoring the inside-kick motion. To provide ground truth, a football...
With growing ageing population, acquiring joint measurements with sufficient accuracy for reliable gait assessment is essential. Additionally, the quality of gait analysis relies heavily on accurate feature selection and classification. Sensor-driven and one-camera optical motion capture systems are becoming increasingly popular in the scientific literature due to their portability and cost-efficacy...
For real-time feedback and cost-efficient analysis from sport videos, it is essential to automatically identify players. In this paper, we propose a method for identifying sport players in videos. Our method uses wearable sensors to obtain their motions. Player identification is achieved by motion feature matching between (unknown) players in videos and wearable sensors whose IDs are already known...
This paper proposes a method for human activity classification in home based monitoring. The proposed approach is based on minimum jerk (MinJerk), a primary model for smooth path planning employed by human motor control in upper-extremity motion. Based on new evidences that show common control strategies in lower and upper extremity, MinJerk is adapted in our study to estimate the foot motion with...
Conventional methods of gait analysis for person identification use features extracted from a sequence of camera images taken during one or more gait cycles. An implicit assumption is made that the walking direction does not change. However, cameras deployed in real-world environments (and often placed at corners) capture images of humans who walk on paths that, for a variety of reasons, such as turning...
Foot clearance parameters provide useful insight into tripping risks during walking. This paper proposes a technique for the estimate of key foot clearance parameters using inertial sensor (accelerometers and gyroscopes) data. Fifteen features were extracted from raw inertial sensor measurements, and a regression model was used to estimate two key foot clearance parameters: First maximum vertical...
For a grammar-based approach to the recognition of visual events, there are two major limitations that prevent it from real application. One is that the event rules are predefined by domain experts, which means huge manual cost. The other is that the commonly used grammar can only handle sequential relations between subevents, which is inadequate to recognize more complex events involving parallel...
This paper introduces an algorithm for detecting walking motion using point trajectories in video sequences. Given a number of point trajectories, we identify those which are spatio-temporally correlated as arising from feet in walking motion. Unlike existing techniques we do not assume clean point tracks but instead propose “probabilistic trajectories” as new features to classify. These are extracted...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.