Browsing by Author "Kurt, Mehmet Can"

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Open Access
A key-pose based representation for human action recognition
(2011) Kurt, Mehmet Can
This thesis utilizes a key-pose based representation to recognize human actions in videos. We believe that the pose of the human figure is a powerful source for describing the nature of the ongoing action in a frame. Each action can be represented by a unique set of frames that include all the possible spatial configurations of the human body parts throughout the time the action is performed. Such set of frames for each action referred as “key poses” uniquely distinguishes that action from the rest. For extracting “key poses”, we define a similarity value between the poses in a pair of frames by using the lines forming the human figure along with a shape matching method. By the help of a clustering algorithm, we group the similar frames of each action into a number of clusters and use the centroids as “key poses” for that action. Moreover, in order to utilize the motion information present in the action, we include simple line displacement vectors for each frame in the “key poses” selection process. Experiments on Weizmann and KTH datasets show the effectiveness of our key-pose based approach in representing and recognizing human actions.
Open Access
Mağaza katalogları içerisinde resim arama
(IEEE, 2009-04) Baysal, Sermetcan; Kurt, Mehmet Can; Aydoğdu, Gonca; Damcı, Pelin; Telmen, İlay; Duygulu, Pınar
In this paper, an overview of an application, which aims to make significant improvements on access methods to the online shopping catalogs, is presented. In current online shopping sites, only browsing and semantic based retrieval are provided to the users. In this work, a system is constructed on content based retrieval methods in order to allow users to find a clothing item that they are searching within the online catalogs. The results have came out to be impressive when they are examined by the human eye. This work makes use of existing computer vision techniques and applies them to the area of clothing and shopping to provide users with a useful application. © 2009 IEEE.
Open Access
Recognizing human actions using key poses
(IEEE, 2010) Baysal, Sermetcan; Kurt, Mehmet Can; Duygulu, Pınar
In this paper, we explore the idea of using only pose, without utilizing any temporal information, for human action recognition. In contrast to the other studies using complex action representations, we propose a simple method, which relies on extracting "key poses" from action sequences. Our contribution is two-fold. Firstly, representing the pose in a frame as a collection of line-pairs, we propose a matching scheme between two frames to compute their similarity. Secondly, to extract "key poses" for each action, we present an algorithm, which selects the most representative and discriminative poses from a set of candidates. Our experimental results on KTH and Weizmann datasets have shown that pose information by itself is quite effective in grasping the nature of an action and sufficient to distinguish one from others. © 2010 IEEE.