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.
Transfer Subspace Learning has gained recent popularity in the literature for its ability to perform cross-dataset and cross-domain object recognition — enablers for data fusion. The ability to leverage existing data without the need for additional data collections is attractive for Automatic Target Recognition applications. For Automatic Target Recognition (or object assessment) applications, Transfer...
The ability to classify a vehicle is of extreme importance for both civilian and non-civilian applications. For non-civilian applications the state-of-the-art leaves much to be desired, as hierarchal and real-time classification have yet to be truly investigated. This paper provides a survey of the current state-of-the-art in vehicle classification and provides recommendations for future research...
The ability to classify a dismount and its activity, is of interest for both military and non-military applications. This effort describes a database that is rich for dismount activity classification and is available to the public - the Minor Area Motion Imagery Dismount Tower Data (MAMI-DTD) Collection. The MAMI-DTD collection was gathered in the Summer of 2013 and contains several examples of dismount...
This paper will look at using open source tools (Blender, LuxRender, and Python) to generate a large data set to be used to train an object recognition system. The model produces camera position, camera attitude, and synthetic camera data that can be used for exploitation purposes. We focus on electro-optical (EO) visible sensors to simplify the rendering but this work could be extended to use other...
In this work, we explore low-dimensional representations of high-dimensional data derived from electro-optical synthetic vehicle images. The collection of vehicle images consists of four different vehicle models: Toyota Camry, Toyota Avalon, Toyota Tacoma, and Nissan Sentra. This data contains 3,601 160 × 213 gray-scale vehicle images sampled uniformly over a camera view hemisphere. We use the non-linear...
In this paper we describe preliminary efforts to extend previous gender classification experiments using feature histograms extracted from 3D point clouds of human subjects. The previous experiments used point clouds drawn from the Civilian American and European Surface Anthropometry Project (CAESAR anthropometric database provided by the Air Force Research Laboratory (AFRL) Human Effectiveness Directorate...
In this paper we apply classic image computing methods to a dataset of passive polarmetric long wave infrared data (LWIR). By employing several different pattern recognition techniques such as k-means clustering, support vector machine (SVM), Naive Bayes, and AdaBoost, we demonstrate accurate classification of skin vs. background with an 84% average classification rate. In addition we explored classification...
In this paper we explore the robustness of histogram features extracted from 3D point clouds of human subjects for gender classification. Experiments are conducted using point clouds drawn from the Civilian American and European Surface Anthropometry Resource Project (CAESAR anthropometric database provided by the Air Force Research Laboratory (AFRL) Human Effectiveness Directorate and SAE International)...
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.