Analyzing students’ emotions from classroom videos can help both teachers and parents quickly know the engagement of students in class. The availability of high-definition cameras creates opportunities to record class scenes. However, watching videos is time-consuming, and it is challenging to gain a quick overview of the emotion distribution and find abnormal emotions. In this article, we propose EmotionCues , a visual analytics system to easily analyze classroom videos from the perspective of emotion summary and detailed analysis, which integrates emotion recognition algorithms with visualizations. It consists of three coordinated views: a summary view depicting the overall emotions and their dynamic evolution, a character view presenting the detailed emotion status of an individual, and a video view enhancing the video analysis with further details. Considering the possible inaccuracy of emotion recognition, we also explore several factors affecting the emotion analysis, such as face size and occlusion. They provide hints for inferring the possible inaccuracy and the corresponding reasons. Two use cases and interviews with end users and domain experts are conducted to show that the proposed system could be useful and effective for analyzing emotions in the classroom videos.

EmotionCues : Emotion-Oriented Visual Summarization of Classroom Videos

With the advancement in digital video technology, video surveillance has been playing its vital role for ensuring safety and security. The surveillance systems are deployed in wide range of applications to invigilate stuffs and to analyse the activities in the environment. From the single or multi surveillance camera, a huge amount of data is generated, stored and processed for security purpose. Due to time constraints, it is a very tedious process for an analyst to go through the full content. This limitation has been overcome by the use of video summarization. The video summarization is intended to afford comprehensible analysis of video by removing duplications and extracting key frames from the video. To make an easily interpreted outline, the various available video summarization methods will try to shot the summary of the main occurrences, scenes, or objects in a frame. Depending on the applications, it is required to summarize the happenings in the scene and detect the objects (static/dynamic) which is recorded in the video. Hence this paper provides the various methods used for video summarization and a comparative study of different techniques. It also presents different object detection, object classification and object tracking algorithms available in the literature.

A study on various methods used for video summarization and moving object detection for video surveillance applications

Nowadays, soccer is the most popular sport in our society, followed by millions of people. Consequently, many video analysis applications have been developed in the last years to provide information that can be useful for viewers, referees, coaches and players. Some of these applications are focused on specific tasks, such as detecting players, segmenting the field of play, or registering the broadcast images. On the other hand, there are applications aimed at performing tasks of a higher level, such as event detection or game analysis. Here, the most meaningful techniques and applications that have been proposed throughout the last two decades to analyze soccer video sequences are surveyed. The aim of the paper is not to compare the existing techniques, but to represent a comprehensive and organized showcase for the state-of-the-art in the field: as such, it provides a thorough review of the existing types of soccer analysis applications and the techniques used in each one of them, along with the apparent recent technical trends identified from the most recent works, and discuses the challenges in soccer analysis that still remain unsolved.

Techniques and applications for soccer video analysis: A survey

Intelligent video surveillance system plays a vital role in ensuring safety and security to the public. In recent years, surveillance systems are widely used in all places starting from border security application to street monitoring systems. As the analysis of surveillance video becomes one of the most emerging trends and research fields of interest, there is a need for a comprehensive survey on various works being carried out in the field. A single surveillance camera records the happenings in a particular field of view both day and night at all time, likewise multi-camera environment generates a huge volume of data. Though motion sensitivity based cameras considerably reduce the storage volume, they still produce large volume of data when employed in busy areas. The large amount of video data cannot be fully observed for analysis as it is time overwhelming process. Hence it is required to summarize the activities in the scene and detect unusual events recorded in videos. Hence, this paper discusses various techniques for summarization and unusual event detection in video and it presents current scenario of research in this area. This paper lists out the main focus of various researchers, datasets being used and features being considered for their approaches. It yields the future directions in this area of research, applications of event detection and summarization.

Towards Comprehensive Understanding of Event Detection and Video Summarization Approaches

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Digital Video Summarization Techniques: A Survey

In today's world, the rapid development of digital video and editing technology has led to fast growing of video data, creating the need for effective and advanced techniques for analysis and video retrieval, as multimedia repositories have made browsing, delivery of contents (video) and video retrieval very slow. Hence, video summarization proposes various ways for faster browsing among a large amount of data and also for content indexing. Many people spend their free time to watch or play different sports like soccer, cricket, etc. but it is not possible to watch each and every game due to the longer timing of the game. In such cases, the users may just want to view the summary of the video that is just an abstract of the original video, instead of watching the whole video that provides more information about the occurrence of various incidents in the video. It is preferable to watch just highlights of the game or just review/trailer of a movie. Apparently, summarizing a video is an important process. In this paper, video summarization approaches are discussed, that can generate static or dynamic summaries. We present different techniques for each mode in literature. We have discussed some features used for generating video summaries. As soccer is the world’s most famous game played and watched, it is taken as a case study. Research done in this domain is discussed. We conclude that there is a broad perspective for further research in this field.

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Soudamini Pawar

Papers

Video Summarization: Survey on Event Detection and Summarization in Soccer Videos