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Conventional video tracking operates over RGB or grey-level data which contain significant clues for the identification of the targets. While this is often desirable in a video surveillance context, use of video tracking in privacy-sensitive environments such as hospitals and care facilities is often perceived as intrusive. Therefore, in this work we(More)
Action recognition and video summarization are two important multimedia tasks that are useful for applications such as video indexing and retrieval, video surveillance, human-computer interaction and home intelligence. While many approaches exist in the literature for these two tasks, to date they have always been addressed separately. Instead, in this(More)
Fine-grained activities are human activities involving small objects and small movements. Automatic recognition of such activities can prove useful for many applications, including detailed diarization of meetings and training sessions, assistive human-computer interaction and robotics interfaces. Existing approaches to fine-grained activity recognition(More)
The use of conventional video tracking based on color or gray-level videos often raises concerns about the privacy of the tracked targets. To alleviate this issue, this paper presents a novel tracker that operates solely from depth data. The proposed tracker is designed as an extension of the popular Struck algorithm which leverages the effective framework(More)
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