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.
Due to the prevalence of digital cameras, it is easy to retrieve digital images from the Internet. With the rapid development of digital image processing, databases, and Internet technologies, how to efficiently manage a large amount of digital images is very important. In this paper, we proposed a novel approach for automatic image annotation. We extract color, texture, and shape features from a...
In this paper, we present a graph-based approach to automatically detect defective zebrafish embryos. Here, the zebrafish is segmented from the background using a texture descriptor and morphological operations. In this way, we can represent the embryo shape as a graph, for which we propose a vectorisation method to recover clique histogram vectors for classification. The clique histogram represents...
General object detection still remains a big challenge for vision researchers. In this paper, we are particularly interested in the subject of object detection in the context of street scene. Our image database consists of video frames taken from urban street which tends to be crowded and presents a lot of artificial objects. Traditional street scene understanding methods often involve 3D reconstruction...
We pose the problem of perfect segmentation for regions with ambiguous boundaries. We design machine learning classifiers to identify boundaries and build these into an interactive contouring framework. Experiments using synthetic and multiple sclerosis (MS) textures show the success of the classifiers. Experiments using the contouring tool reveal significant improvement in accuracy and inter/intra-operator...
This paper presents a novel approach to pedestrian classification which involves utilizing the synthesized virtual samples of a learned generative model to enhance the classification performance of a discriminative model. Our generative model captures prior knowledge about the pedestrian class in terms of a number of probabilistic shape and texture models, each attuned to a particular pedestrian pose...
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.