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 present an approach to automatically generating verbal commentaries for tennis games. We introduce a novel application that requires a combination of techniques from computer vision, natural language processing and machine learning. A video sequence is first analysed using state-of-the-art computer vision methods to track the ball, fit the detected edges to the court model, track the players, and...
This paper presents our solution to MSR-Bing Image Retrieval Challenge to measure the relevance of web images and the query given in text form. We compare and integrate three typical methods (SVM-based, CCA-based, PAMIR) to conduct the large-scale cross-modal retrieval task with concept-level visual features. In SVM-based approach, the relevance of the image and the query is scored using an on-line...
Moving vehicle detection is very important for urban traffic surveillance and situational awareness on the battlefield. Algorithms with cascade structure like Adaboost are booming in the recent decade, and successful in realtime application. However, most of them use a sliding window protocol on multi-scale images which involves heavy computing. Therefore, they are only suitable for simple feature...
In this paper we addresses the problem of human action recognition by introducing a new representation of image sequences as a collection of spatiotemporal events that are localized at interest point and using multi-class SVM for classification. The interest points are detected by the SIFT detector and a spatio-temporal interest point detector. We proposed a new bag of words approach to represent...
Visual concept detection is one of the most important tasks in image and video indexing. This paper describes our system in the ImageCLEF@ICPR Visual Concept Detection Task which ranked first for large-scale visual concept detection tasks in terms of Equal Error Rate (EER) and Area under Curve (AUC) and ranked third in terms of hierarchical measure. The presented approach involves state-of-the-art...
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.