Abstract-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.

Tracking multiple players is crucial to analyze soccer videos in real time. Yet, rapid illumination changes and occlusions among players who look similar from a distance make tracking in soccer very difficult. Particle-filter-based approaches have been utilized for their ability in tracking under occlusion and rapid motions. Unlike the common practice of choosing particles on targets, we introduce the notion of shared particles densely sampled at fixed positions on the model field. We globally evaluate targets' likelihood of being on the model field particles using our combined appearance and motion model. This allows us to encapsulate the interactions among the targets in the statespace model and track players through challenging occlusions. The proposed tracking algorithm is embedded into a real-life soccer player tracking system called Sentioscope. We describe the complete steps of the system and evaluate our approach on large-scale video data gathered from professional soccer league matches. The experimental results show that the proposed algorithm is more successful, compared with the previous methods, in multiple-object tracking with similar appearances and unpredictable motion patterns such as in team sports. Index Terms-Model field particles, multiple-object tracking, Sentioscope, soccer player tracking, sports video analysis. I. INTRODUCTION S OCCER (football) is among the world's most popular sports played by millions of people around the world. Such popularity has led many computer vision researchers to work on soccer video analysis. A wide spectrum of such applications has been introduced to offer team/player performance analysis, referee decision support, video summarization, highlight extraction, and intelligent broadcast cameras [1]. Team/player performance measurement systems has the potential to reveal aspects of the game that are not obvious to the human eye. Such systems can measure the distance covered by players, speed of movement, number of sprints, and players' relative positioning with respect to others. This data are then used in individual player performance evaluation, fatigue detection, assessment of team's tactical performance and analysis of the opponents. Accurate tracking of multiple soccer players in real time is the key issue in performance evaluation, and requires detecting Manuscript

In this paper, we utilize a line based pose representation to recognize human actions in videos. We represent the pose in each frame by employing a collection of line-pairs, so that limb and joint movements are better described

ÖzetçeBu makalede internetteki giysi kataloglarına eri im yöntemleri üzerinde olumlu de i ikler yapmayı amaçlayan bir uygulamadan bahsedilmektedir. Hâlihazırdaki internet satı siteleri kullanıcılara giysi koleksiyonlarını sadece gezme ve metin bazlı arama imkânı vermektedirler. Bu çalı mada ise ma aza koleksiyonları üzerinde içerik bazlı bir arama sistemi geli tirilmi ve kullanıcılara aradıkları bir giysiyi bulma imkânı tanınmı tır. Deney sonuçları göz ile incelendi inde tatmin edici ba arı oranlarına ula ılmı tır. Bu çalı ma, bilinen bilgisayarla görme tekniklerini farklı bir alana uygulayarak günlük hayatta kullanılabilecek ve insanlara faydalı olabilecek bir uygulama ortaya çıkmı tır. AbstractIn 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.

Özetçe Bilgisayarla görme teknikleri kullanan sporcu takip sistemleri farklı yöntemler kullanarak oyuncuları arka plandan ayıklamakta ve daha sonra otomatik olarak takip etmektedir. Oyuncuların performansları hesaplanmak istenildiğinde, takip edilen oyuncunun bir video karesi üzerinde göründüğü koordinatları bilmek yeterli olmamaktadır. Piksel cinsinden olan resim koordinatlarının oyuncunun saha üzerindeki yerini temsil eden gerçek dünya koordinatlarına çevrilmesi gerekmektedir. Futbol sahasının düzlemsel olduğunu ön bilgisini kullanarak, resim koordinat sistemi ve gerçek dünya koordinat sistemi arasındaki ilişkilendirme, düzlemsel homografi ile kurulabilir. Bu makalede, üç kameradan oluşan bir futbolcu takip sisteminin gerçek saha modeli ile arasındaki homografinin hesaplanması üzerine bir tartışma sunulmaktadır. AbstractComputer vision based athlete tracking systems use different methods to segment players from the background and then track them automatically throughout the video. It is insufficient to know a player's position on the image plane if we want to extract performance analysis of the player. Furthermore, image plane coordinates need to be transformed to real world coordinates representing the position of the player on the field. Knowing that the soccer field is planar, the mapping between the world coordinate system and the image coordinate system can be described by a planar homography. In this paper, we provide a discussion on homography calculations between a three-camera player tracking system and the real world soccer field model.