This paper focuses on methods that can be used in football analysis by showing our implementation and results of automatic football video registration and player detection. Some of the first methods we implemented like SIFT Feature detection for video registration and background detection for player detection were not successful. However, we implemented more integrated methods like line mapping...

The scale invariant feature transform and the integral invariants are two well known approaches for visual feature extraction. Each of these approaches has been successfully applied to global localization of mobile robots. In this paper, we propose applying a combination of the two concepts. We demonstrate that extracting the integral invariants from the scale space does indeed improve the loca...

Matching precision of scale-invariant feature transform (SIFT) is evaluated and improved in this paper. The aim of the paper is not to invent a new feature detector more invariant than the others. Instead, we focus on SIFT method and evaluate and improve the matching precision, defined as the root mean square error (RMSE) under ground truth geometric transform. Matching precision reflects to so...

This paper shows that the common task of interest region matching using local descriptors can be improved using a new similarity measure. The similarity measure is motivated by the information theoretic image alignment that maximize mutual information between images. A property of the mutual information metric is that it does not only depend on how similar the signals are but also how complex t...

In this chapter, we continue the discussion on medium access control protocols designed for wireless sensor networks. This builds upon the background material and protocols presented in Chapter 4. We first present protocols that are based on random access techniques such as Carrier Sense Multiple Access. These include the Sift protocol, the T-MAC protocol and other protocols. The second set of ...

Violent scene detection (VSD) is a challenging problem because of the heterogeneous content, large variations in video quality, and semantic meaning of the concepts. The Violent Scenes Detection Task of MediaEval [1] provides a common dataset and evaluation protocol thus enables a fair comparison of methods. In this paper, we describe our VSD system used in MediaEval 2014 and briefly discuss th...

For the plant task of the LifeCLEF challenge, we adopted the reference Bag-of-Word framework (BoW) with local soft assignment. The points of interests (POI) are both detected and described with the SIFT and OpponentColor SIFT. Parameters of the bag of word are optimized through cross-validation and we present the results of different experimentations. A Support Vector Machine is trained with di...