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Proceedings ArticleDOI

Human motion analysis: a review

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TLDR
The paper gives an overview of the various tasks involved in motion analysis of the human body, and focuses on three major areas related to interpreting human motion: motion analysis involving human body parts, tracking of human motion using single or multiple cameras, and recognizing human activities from image sequences.
Abstract
Human motion analysis is receiving increasing attention from computer vision researchers. This interest is motivated by a wide spectrum of applications, such as athletic performance analysis, surveillance, man-machine interfaces, content-based image storage and retrieval, and video conferencing. The paper gives an overview of the various tasks involved in motion analysis of the human body. The authors focus on three major areas related to interpreting human motion: 1) motion analysis involving human body parts, 2) tracking of human motion using single or multiple cameras, and 3) recognizing human activities from image sequences. Motion analysis of human body parts involves the low-level segmentation of the human body into segments connected by joints, and recovers the 3D structure of the human body using its 2D projections over a sequence of images. Tracking human motion using a single or multiple camera focuses on higher-level processing, in which moving humans are tracked without identifying specific parts of the body structure. After successfully matching the moving human image from one frame to another in image sequences, understanding the human movements or activities comes naturally, which leads to a discussion of recognizing human activities. The review is illustrated by examples.

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Citations
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The State of the Art in Multiple Object Tracking Under Occlusion in Video Sequences

TL;DR: This paper reviews existing techniques and systems for tracking multiple occlusion objects using one or more cameras and identifies what appear to be the most promising approaches for tracking in general and for soccer in ball game applications.
Proceedings ArticleDOI

Searching Video for Complex Activities with Finite State Models

TL;DR: A method of representing human activities that allows a collection of motions to be queried without examples, using a simple and effective query language, based on units of activity at segments of the body that can be composed across space and across the body to produce complex queries is described.
Patent

Multichannel acoustic echo reduction

TL;DR: In this paper, a multichannel acoustic echo reduction system is described, which includes an acoustic echo canceller (AEC) component having a fixed filter for each respective combination of loudspeaker and microphone signals and having an adaptive filter for every microphone signal.
Proceedings ArticleDOI

Recent advances in video-based human action recognition using deep learning: A review

TL;DR: This paper presents a review of various state-of-the-art deep learning-based techniques proposed for human action recognition on three types of datasets, namely, single viewpoint, multiple viewpoint and RGB-depth videos.
Journal ArticleDOI

Employing a RGB-D sensor for real-time tracking of humans across multiple re-entries in a smart environment

TL;DR: This paper intends to tackle the problems of detecting and tracking humans in a realistic home environment by exploiting the complementary nature of (synchronized) color and depth images produced by a low-cost consumer-level RGB-D camera by selectively feeding the complementary data emanating from the two vision sensors to different algorithmic modules.
References
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Proceedings ArticleDOI

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Journal ArticleDOI

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