29,196 research outputs found
Ranking algorithms for implicit feedback
This report presents novel algorithms to use eye movements as an implicit relevance feedback in order to improve the performance of the searches. The algorithms are evaluated on "Transport Rank Five" Dataset which were previously collected in Task 8.3. We demonstrated that simple linear combination or tensor product of eye movement and image features can improve the retrieval accuracy
Toward next generation coaching tools for court based racquet sports
Even with todayâs advances in automatic indexing of multimedia content, existing coaching tools for court sports lack the ability to automatically index a competitive match into key events. This paper proposes an automatic event indexing and event retrieval system
for tennis, which can be used to coach from beginners upwards.
Event indexing is possible using either visual or inertial sensing, with the latter potentially providing system portability. To achieve maximum performance in event indexing, multi-sensor data integration is implemented, where data from both sensors is merged to automatically index key tennis events. A complete event retrieval
system is also presented to allow coaches to build advanced queries which existing sports coaching solutions cannot facilitate without an inordinate amount of manual indexing
Childrenâs information retrieval: beyond examining search strategies and interfaces
The study of childrenâs information retrieval is still for the greater part untouched territory. Meanwhile, children can become lost in the digital information world, because they are confronted with search interfaces, both designed by and for adults. Most current research on childrenâs information retrieval focuses on examining childrenâs search performance on existing search interfaces to determine what kind of interfaces are suitable for childrenâs search behaviour. However, to discover the true nature of childrenâs search behaviour, we state that research has to go beyond examining search strategies used with existing search interfaces by examining childrenâs cognitive processes during information-seeking. A paradigm of childrenâs information retrieval should provide an overview of all the components beyond search interfaces and search strategies that are part of childrenâs information retrieval process. Better understanding of the nature of childrenâs search behaviour can help adults design interfaces and information retrieval systems that both support childrenâs natural search strategies and help them find their way in the digital information world
An automatic visual analysis system for tennis
This article presents a novel video analysis system for coaching tennis players of all levels, which uses computer vision algorithms to automatically edit and index tennis videos into meaningful annotations.
Existing tennis coaching software lacks the ability to automatically index a tennis match into key events, and therefore, a coach who uses existing software is burdened with time-consuming manual video editing. This work aims to explore the effectiveness of a system to automatically detect tennis events. A secondary aim of this work is to explore the bene- fits coaches experience in using an event retrieval system to retrieve the automatically indexed events. It was found that automatic event detection can significantly improve the experience of using video feedback as part of an instructional coaching session. In addition to the automatic detection of key tennis events, player and ball movements are automati- cally tracked throughout an entire match and this wealth of data allows users to find interesting patterns in play. Player and ball movement information are integrated with the automatically detected tennis events, and coaches can query the data to retrieve relevant key points during a match or analyse player patterns that need attention. This coaching software system allows coaches to build advanced queries, which cannot be facilitated with existing video coaching solutions, without tedious manual indexing. This article proves that the event detection algorithms in this work can detect the main events in tennis with an average precision and recall of 0.84 and 0.86, respectively, and can typically eliminate man- ual indexing of key tennis events
The Evolution of First Person Vision Methods: A Survey
The emergence of new wearable technologies such as action cameras and
smart-glasses has increased the interest of computer vision scientists in the
First Person perspective. Nowadays, this field is attracting attention and
investments of companies aiming to develop commercial devices with First Person
Vision recording capabilities. Due to this interest, an increasing demand of
methods to process these videos, possibly in real-time, is expected. Current
approaches present a particular combinations of different image features and
quantitative methods to accomplish specific objectives like object detection,
activity recognition, user machine interaction and so on. This paper summarizes
the evolution of the state of the art in First Person Vision video analysis
between 1997 and 2014, highlighting, among others, most commonly used features,
methods, challenges and opportunities within the field.Comment: First Person Vision, Egocentric Vision, Wearable Devices, Smart
Glasses, Computer Vision, Video Analytics, Human-machine Interactio
Real-time 3D Face Recognition using Line Projection and Mesh Sampling
The main contribution of this paper is to present a novel method for automatic 3D face recognition based on sampling a 3D mesh structure in the presence of noise. A structured light method using line projection is employed where a 3D face is reconstructed from a single 2D shot. The process from image acquisition to recognition is described with focus on its real-time operation. Recognition results are presented and it is demonstrated that it can perform recognition in just over one second per subject in continuous operation mode and thus, suitable for real time operation
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