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Topics about health, music, sport, and technology are widely discussed in social network sites, especially in Twitter. Sharing information about those topics can enrich one's knowledge as well as increase the awareness of the current trends pertinent to the area of interests. Hence, this research aims to develop a web-based application that can classify tweets of netizens into these four categories...
Sporting events evoke strong emotions amongst fans and thus act as natural laboratories to explore emotions and how they unfold in the wild. Computational tools, such as sentiment analysis, provide new ways to examine such dynamic emotional processes. In this article we use sentiment analysis to examine tweets posted during 2014 World Cup. Such analysis gives insight into how people respond to highly...
We present a robust multimodal approach for classifying the sport genre in videos recorded by mobile phone users at a sport event. In addition to traditional audio-visual content analysis tools, we propose to analyze auxiliary sensor data (electronic compass data and accelerometer data) captured simultaneously with the video recording. By means of machine learning techniques, we build models of visual...
Smart phones are increasingly being used to track and recognize different types of activity. However, the task of using smart phones to infer the intensity of sport activities has not received a lot of attention yet. Therefore, we study how off-the-shelf smart phones with built-in accelerometers can be used to estimate the intensity of recreational sport activities. We focus on finding the most appropriate...
The ads exposure frequency in a TV is very important for the pricing of the advertising. If we count this exposure frequency by person, it will be very time consuming and error-prone. In this paper, we propose an approach and design a system for searching and counting the number of banner ads appearing in sports videos. The searching proceeds by matching feature points from pre-specified sample ads...
In this paper, we propose a method to track multiple players in a football match video which is captured by a single camera. The camera pans and brings the players and the ball into the view, enabling to record the whole pitch. The players' trajectories in frames and camera movement are obtained to estimate the trajectories on the pitch. Moreover, we propose an effective tracking method for solving...
In this paper a visual self-localization method for a humanoid robot is presented. This one is based on monocular information. The goal of this method is to obtain the position (x; y) and orientation θ of the humanoid robot inside the field of play. The methods proposed include some digital image processing algorithms and geometric interpretation to perform a 3D monocular reconstruction, that allows...
To detect and annotate the key events of live sports videos, we need to tackle the semantic gaps of audio-visual information. Previous work has successfully extracted semantic from the time-stamped web match reports, which are synchronized with the video contents. However, web and social media articles with no time-stamps have not been fully leveraged, despite they are increasingly used to complement...
In tennis match highlights mainly take place in shots containing full court (Court view shots), therefore successful court view shots detection is useful for highlights extraction. This paper proposes a court view shots detection algorithm, in which shot detection that is the precondition of usual shot classification is given up for shot detection not only costs more time, but also its detection performance...
In this paper, a method combining PnP and OI algorithms is developed to measure the pose of a humanoid robot in high precision in order to play table tennis. The PnP-based algorithm is employed to obtain the rough pose, which is taken as the initial value of the OI algorithm. The OI algorithm optimizes the result in order to ensure the orthogonal orientation matrix of the pose. Considering the real-time,...
The exact height measurement of a golf ball impacted in a golf simulator system is an important factor in determining the trajectory of ball. However, finding the height of a golf ball in a planar sensor using a light, poses many obstacles. In this paper, therefore, to find the height of a golf ball, the method of estimating the vertical launch angle of a ball is proposed. The flying time of a ball,...
This paper presents a novel method for semantic understanding of sports matches by extracting and ranking events within a match by interestingness. Using audio feature extraction, a system is presented which is able to segment between studio and pitch side broadcast. Key events within Rugby Union matches are then identified based on crowd excitation levels and referee whistles. This identifies individual...
This paper proposes a method to deal with the problem of sports classification through audio analysis. First, a two-pass audio segmentation module is developed as the front-end to extract announcer's speech from the audio streams. Then speech recognition technology is employed on the speech segments to extract keywords which are used as features to distinguish different sports. Finally, based on the...
Soccer highlight detection is an active research topic in recent years. In this paper, we present our effort to detect an important audio keyword - excited commentator speech, which contributes to a state-of-the-art soccer highlight extraction system. We propose an approach of using statistical classifier based on Gaussian mixture models (GMMs) with unsupervised model adaptation. The excited speech...
With the explosion in demand for visual information retrieval in soccer videos, many Content-Based Video Retrieval (CBVR) models were born. However these current CBVR models still remain some shortcomings such as inflexible retrieval frameworks because they are majorly based on a specific training data set and a specific language. In this paper we propose a framework which contains flexible and easy-to-use...
On-screen text is a rich information resource to query events in soccer video due to its close relation to what happens on the screen. However, low resolution, clutter background, unknown font, size, color, etc. prevent the efforts of using this resource for querying. This paper presents a novel approach for querying events in soccer video using on-screen texts. The proposed approach is completely...
A critical issue of measuring video similarity is most video data are huge files, which vary in terms of length and amount of data, resulting in time-consuming data processing. Therefore, reducing the dimensionality of the data becomes a necessity. This paper proposes the video similarity measurement approach for sports video classification by dimensionality reduction with distance space and random...
Tactic analysis is receiving more attention in sports video analysis for its assistance to coaches and players. This paper proposes an efficient key sub-trajectory feature representation of ball trajectory for tactic analysis. Ball trajectories are modeled with the generalized suffix tree where frequent sub-trajectory patterns are searched for. Key sub-trajectory patterns are extracted by further...
Human action recognition is an important research area in the field of computer vision having a great number of real-world applications. This paper presents a multi-view action recognition framework that extracts human silhouette clues from different cameras, analyzes scene dynamics and interprets human behaviors by the integration of multivariate data in fuzzy rule-based system. Different features...
We explore the benefits of using contextual features for head pose estimation in football games. Contextual features are derived from knowledge of the position of all players and combined with image based features derived from low-resolution footage. Using feature selection and combination techniques, we show that contextual features can aid head pose estimation in football games and potentially be...
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