Monitoring human activities finds novel applications in smart environment settings. Examples include immersive multimedia and virtual reality, smart buildings and occupancy-based services, assisted living and patient ...
详细信息
Monitoring human activities finds novel applications in smart environment settings. Examples include immersive multimedia and virtual reality, smart buildings and occupancy-based services, assisted living and patient monitoring, and interactive classrooms and teleconferencing. A network of cameras can enable detection and interpretation of human events by utilizing multiple views and collaborative processing. distributedprocessing of acquired videos at the source camera facilitates operation of scalable vision networks by avoiding transfer of raw images. This allows for efficient collaboration between the cameras under the communication and latency constraints, as well as being motivated by aiming to preserve the privacy of the network users (no image transfer out of the camera) while offering services in applications such as assisted living or virtual placement. In this paper, collaborative processing and data fusion techniques in a multicamera setting are examined in the context of human pose estimation. Multiple mechanisms for information fusion across the space (multiple views), time, and different feature levels are introduced to meet system constraints and are described through examples.
We are interested in building scalable computer vision systems for distributedprocessing of big visual data. We apply data streaming concepts, namely stream algebra operators, which have been proven effective in the ...
详细信息
ISBN:
(纸本)9781450347860
We are interested in building scalable computer vision systems for distributedprocessing of big visual data. We apply data streaming concepts, namely stream algebra operators, which have been proven effective in the database literature. The operators collectively form an algebra over data streams. The algebra has well defined semantics. It naturally describes online computer vision algorithms and their feedback control and tuning algorithms. In this work, we present the first implementation of such algebra at large scale. Our implementation provides a high level programming interface for constructing and executing vision workflow graphs while hiding the data transfer and concurrency details. It also allows feedback control and dynamic reconfiguration of vision algorithms. A case study is discussed showing a streaming workflow for online lane and road boundary detection and describing the flexibility and effectiveness of the algebra for building complex distributed applications.
暂无评论