The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper aims to identify the pose of a football player from a video still image. The Random Fern Forest classifier is used in conjunction with a set of 3d person models to produce a pose estimation of the football player. This is a quick classifier so can be used in applications that are required to run in a very short time.
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...
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...
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...
Searching a required image based on the content and visual meaning of the image is challenging. One of the complex groups of images is sport image since a sport image may contain various relevant information such as players' postures, textures and color of players' clothes, and complicated background ground. Achieving high recognition rate depends upond the features extracted from the image. In this...
Sub-pixel detection of target points is the performance bottleneck in camera calibration. Traditional algorithms are computational expensive or low precision when we do camera calibration in sport video analysis. In this paper, we propose a new algorithm to detect the grid-like target (i.e. tennis court in TV broadcasting). It has 3 parts: (1) color histogram based interested point classifier making...
A supervised softbot utilized for analyzing, segmenting, and properly classifying video clips pertaining to a wide variety of sporting events is presented. First, selected action scenes (i.e., training sequences) of a given sporting event are automatically segmented into real-world objects representing the participants of the activity. These objects correspond to the players, the playing field (or...
Producing large amounts of digital media data every day requires fast transmission, efficient storage, flexible manipulation, and reuse of visual content. Since humans tend to use high-level semantic concepts when querying and browsing multimedia databases, there is an increasing need for semantic video indexing and analysis. For this purpose, we proposed a unified framework for semantic extraction...
We propose an automatic soccer video summarization engine which relies on an improved algorithm for the detection of replay shots which delineate interesting events. Video shots are first detected using dominant color and histogram intersection methods. Replay shots are detected using an improved technique, then processed through a set of mid-level descriptors (goal-mouth and score board with other...
This paper proposed a framework for goal event detection in soccer videos by using multi-clues detection rules. In this framework, the visual clues including shot segmentation, shot classification and goal detection is extracted. Meanwhile, the audio clues including the audience's cheering and the commentator' excited speech are extracted. Then the goal event detection rules are defined by combining...
This paper presents extensive experiments on sport event images using the bag-of-words model. We propose a simple but effective combination of feature extraction and visual dictionary formation to boost the performance of naive Bayes classifier based on BOW model. Despite of not being a novel idea, our algorithm offers encouraging performance in event recognition domain. Moreover, in certain degrees,...
With popularization of multimedia devices, semantic analysis of sports video has been widely studied. In this paper, we propose a highlight generation method for basketball games. To create a video highlight, the proposed method selects interesting shots by modeling excitements of the game using score information. For this purpose, a video is first segmented into shots and classified as play and nonplay...
Classifying video content into different semantic granularities is a possible way for flexible video indexing, browsing and retrieval. In this paper, a placed kick refinement algorithm is proposed after semantic based event detection or manually annotation. The placed kick event is further classified into following three types: free kick, corner kick and penalty according to the ball and field lines...
Unsupervised detection of pan and zoom in soccer sequences allows automatic classification of shots and match analysis. In this work we propose a pan and zoom (both in and out) detector specifically designed for low resolution soccer sequences. Our implementation is based on the analysis of the distribution of the motion vectors, already available in the encoded sequence, among a specific subset of...
Our paper presents a new approach for the recognition of highlights in soccer video. Our contribution consists of the combination of Bayesian theorem inferences and Hidden Markov Models (HMMs). We build HMMs to calculate probabilities that a test video segment belongs to highlight and non highlight classes. Then, we apply the Bayesian theorem on the two previous probabilities. Our system has achieved...
This paper presents an illumination adaptive color object recognition method for robot soccer match. Generally, the colors are identified by referring to the pre-defined bounds for the components of each color. However, it is not an easy work to define non-interfered bounds for different colors, and the bounds are sensitive to illumination conditions. Instead, in this work, different colors are discriminated...
An automatic pitch type recognition system has been developed. It is difficult to determine the pitch type automatically from a baseball broadcast video, so the decision is currently made by specialists that have expertise and experience in baseball. We developed a system incorporating expertise of professionals. The system identifies pitch type, such as straight balls and curveballs, from single-view...
In this paper, we propose a novel hierarchical framework for soccer (football) video classification. Unlike most existing video classification approaches, which focus on shot detection followed by classification based on clustering using shot aggregation, the proposed scheme perform a top-down video scene classification which avoids shot clustering. This improves the classification accuracy and also...
In this paper, we propose a method to acquire the possession information in different zones of the playfield from soccer video by using view type and playfield zone mid-level descriptors. First, each video frame is classified into three kinds of view type according to a domain-specific feature, grass area ratio and series of classification rules. Then, the classified frames are used to determine the...
Optimizing vision processing is crucial for real-time performance of robots in RoboCuppsilas small-size league (SSL). We describe in this paper our current approach to improve visual processing in ITAMpsilas Eagle Knights SSL team. We describe our use of a neural network to classify camera image pixels to a discrete set of color classes that is robust under different light conditions. We show how...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.