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Activity recognition from first-person (ego-centric) videos has recently gained attention due to the increasing ubiquity of the wearable cameras. There has been a surge of efforts adapting existing feature descriptors and designing new descriptors for the first-person videos. An effective activity recognition system requires selection and use of complementary features and appropriate kernels for each...
Content-based video copy detection (CBCD) has an important role especially in distributing and tracking of copyright and commercial videos. Basically, two main descriptors are used for CBCD one of which, using the interest points in keyframes, the other using the content of a whole keyframe. Even if the local descriptor-based approaches have good results in CBCD problem, it takes too much time for...
Better ways of representing the results of image search can be found rather than regular lists of thumbnails. For this purpose, we propose a hierarchical visualisation scheme with two stages. We utilise the notion of image community and aim to detect communities within a large set of images by means of a novel deterministic community detection method. After image communities are detected, the representative...
In this work, we propose a novel community detection method that is specifically designed for image communities. We define image community as a coherent subgroup of images within a large set of images. In order to detect image communities, we construct an image graph by utilizing visual affinity between each image pair and then prune most of the links. Instead of affinity values, we prefer ranking...
In this work, we propose a new method which can detect image communities inside an image set. The proposed method differs from previous works by representing image relations with directed graphs and performing community anaysis on these directed graphs. By analyzing resulting image communities, we can observe the robustness of the proposed method against image deformations (e.g. cutting, text overlay,...
Concept detection stands as an important problem for efficient indexing and retrieval in large video archives. In this work, the KavTan System, which performs high-level semantic classification in one of the largest TV archives of Turkey, is presented. In this system, concept detection is performed using generalized visual and audio concept detection modules that are supported by video text detection,...
Fight detection is an important topic for surveillance systems. However, there has been little success in creating an algorithm that can detect fight in surveillance videos with high performance. In this work, we propose a new method for the task of fight detection in surveillance videos. The proposed method relies on a novel motion feature, namely Motion Co-Occurrence Feature (MCF). Firstly, motion...
Fight detection is still an open problem for video concept detection. There has been little success in creating an algorithm that can detect fight in surveillance videos, movies, or TV broadcasts with high performance values. In this paper, we propose a new method for this task. Firstly, motion vectors are extracted by using optical flow block matching algorithm for the consecutive frames. Secondly,...
Concept detection stands as an important problem for many applications like efficient indexing and retrieval in large video archives. In this work, for detection of diverse and distinct concepts a concept detection system (KavTan) that combines a variety of information sources under a single structure is proposed. The proposed system consists of Generalized Audio Concept Detection and Audio Keyword...
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