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 propose a machine learning based approach to real-time detection and classification assistance for images from unknown environments. While systems for detecting and classifying regular structures like faces in still images are well established, the task of e. g. detecting new morphotypes/objects in an environment is much more complex. The morphotypes/objects are not guaranteed to have apriori known...
This paper presents a method for detecting a pedestrian by leveraging multi-spectral image pairs. Our approach is based on the observation that a multi-spectral image, especially far-infrared (FIR) image, enables us to overcome inherent limitations for pedestrian detection under challenging circumstances, such as even dark environments. For that task, multi-spectral color-FIR image pairs are used...
With the rapid increase of multimedia data, textual content in an image has become a very important source of information for several applications like navigation, image search and retrieval, image understanding, captioning, machine translation and several others. Scene text localization is the first step towards such applications and most current methods focus on generating a small set of high precision...
The color constancy problem is addressed by structured-output regression on the values of the fully-connected layers of a convolutional neural network. The AlexNet and the VGG are considered and VGG slightly outperformed AlexNet. Best results were obtained with the first fully-connected “fc6” layer and with multi-output support vector regression. Experiments on the SFU Color Checker and Indoor Dataset...
Background subtraction (BS) is one of the key steps for detecting moving objects in video surveillance applications. In the last few years, many BS methods have been developed to handle the different challenges met in video surveillance but the role and the relevance of the visual features used has been less investigated. In this paper, we present an Online Weighted Ensemble of One-Class SVMs (Support...
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.