Browsing by Author "Zitouni, Hilal"
Now showing 1 - 5 of 5
Results Per Page
Sort Options
Item Open Access Naming faces on the web(Bilkent University, 2010) Zitouni, HilalIn this study, we introduce a method to name less-frequently appearing people on the web via naming frequently appearing ones first. Current image search engines are widely used for querying a person, however; retrievals are based on textual content; therefore, the results are not satisfactory. On the other hand, although; face recognition is a long standing problem; it is tested for limited sizes and successful results are acquired just for face images captured under controlled environments. Faces on the web, contrarily are huge in amount and vary in pose, illumination, occlusion and facial attributes. Recent researches on the area, suggest not to use simply the visual or textual content alone, but to combine them both. With this approach, face recognition problem is simplified to a face-name association problem. Following these approaches, in our method textual and visual information is combined to name faces. We divide the problem into two sub problems, first the more frequently appearing faces, then the less-frequently appearing faces on the web images are named. A supervised algorithm is used for naming a specified number of categories belonging to more frequently appearing faces. The faces that are not matched with any category are then considered to be the less-frequently appearing faces and labeled using the textual content. We extracted all the names from textual contents, and then eliminate the ones used to label frequentlyappearing faces before. The remaining names are the candidate categories for lessfrequently appearing faces. Each detected less-frequently appearing face finally matched to the names extracted from their corresponding textual content. In order to prune the irrelevant face images, finally, the most similar faces among this collection are found to be matched with their corresponding category. In our experiments, the method is applied on two different datasets. Bothdatasets are constructed from the images captured in realistic environments, varying in pose, illumination, facial expressions, occlusions and etc. The results of the experiments proved that the combination of textual and visual contents on realistic face images outperforms the methods that use either one of them. Besides, handling the face recognition problem as a face-name association, improves the results for the face images collected from uncontrolled environments.Item Open Access Re-ranking of web image search results using a graph algorithm(IEEE, 2008-12) Zitouni, Hilal; Sevil, Sare; Özkan, Derya; Duygulu, PınarWe propose a method to improve the results of image search engines on the Internet to satisfy users who desire to see relevant images in the first few pages. The method re-ranks the results of text based systems by incorporating visual similarity of the resulting images. We observe that, together with many unrelated ones, results of text based systems include a subset of correct images, and this set is, in general, the largest one which has the most similar images compared to other possible subsets. Based on this observation, we present similarities of all images in a graph structure, and find the densest component that corresponds to the largest set of most similar subset of images. Then, to re-rank the results, we give higher priority to the images in the densest component, and rank the others based on their similarities to the images in the densest component. The experiments are carried out on 18 category of images from [8]. © 2008 IEEE.Item Open Access Recognizing faces in news photographs on the web(IEEE, 2009-09) Zitouni, Hilal; Bulut, Muhammed Fatih; Duygulu, PınarWe propose a graph based method in order to recognize the faces that appear on the web using a small training set. First, relevant pictures of the desired people are collected by querying the name in a text based search engine in order to construct the data set. Then, detected faces in these photographs are represented using SIFT features extracted from facial features. The similarities of faces are represented in a graph which is then used in random walk with restart algorithm to provide links between faces. Those links are used for recognition by using two different methods. © 2009 IEEE.Item Open Access Resim arama sonuçlarının çizge tabanlı bir yöntemle yeniden sıralanması(IEEE, 2008-04) Sevil, Sare; Zitouni, Hilal; İkizler, Nazlı; Özkan, D.; Duygulu, PınarArama motorları aracılığı ile arama yapmak günümüzde internetin en yaygın kullanım amaçlarından biridir. Ancak sorgu sonuçları, özellikle resim arama sorgularında, çoğu zaman sorgu ile ilgli olmayan sonuçlar da içerebilmektedir. Bu çalışma, resimsel aramalarda sorguyla ilgili olmayan yanlış sonuçların belirlenmesini ve tekrar sıralama yöntemleri ile sonuç sıralamasının iyileştirilmesini amaçlamaktadır. Yöntem resimsel benzerliklerin bir çizge ile gösterilmesi ve daha sonra sorguya doğru olarak karşılık gelmesi beklenen en benzer resimlerin çizgedeki en yoğun bileşen olarak bulunması esasına dayanmaktadır. Although one of the most common usages of Internet is searching, especially in image search, the users are not satisfied due to many irrelevant results. In this paper we present a method to identify irrelevant results of image search on the İnternet and re-rank the results so that the relevant results will have a higher priority within the list. The proposed method represents the similarity of images in a graph structure, and then finds the densest component in the graph representing the most similar set of images corresponding to the query. ©2008 IEEE.Item Open Access Tag suggestr: Automatic photo tag expansion using visual information for photo sharing websites(Springer, 2008-12) Küçüktunç, Onur; Sevil, Sare G.; Tosun, A. Burak; Zitouni, Hilal; Duygulu, Pınar; Can, FazlıIn this paper, we propose an automatic photo tag expansion system for the community photo collections, such as Flickr. Our aim is to suggest relevant tags for a target photograph uploaded to the system by a user, by incorporating the visual and textual cues from other related photographs. As the first step, the system requires the user to add only a few initial tags for each uploaded photo. These initial tags are used to retrieve related photos including the same tags in their tag lists. Then the set of candidate tags collected from a large pool of photos is weighted according to the similarity of the target photo to the retrieved photo including the tag. Finally, the tags in the highest rankings are used to automatically expand the tags of the target photo. The experimental results on Flickr photos show that, the use of visual similarity of semantically relevant photos to recommend tags improves the quality of suggested tags compared to only text-based systems. © 2008 Springer Berlin Heidelberg.