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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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Patent

3D gaze tracker

TL;DR: In this article, a gaze tracker for determining a gaze vector for a person is presented, which comprises a 3D camera that and a picture camera that image the person and a controller that processes images acquired by the cameras to determine a gaze direction and origin for the gaze vector.
Journal ArticleDOI

Children's intuitive gestures in vision-based action games

TL;DR: This research presents four novel computer vision-based game technologies that aim to give players more immersive and physically challenging gaming experiences.
Journal ArticleDOI

A survey of energy-efficient context recognition systems using wearable sensors for healthcare applications

TL;DR: A new classification of the energy-efficient mechanisms for health-related human context recognition applications for wearable sensor networks is proposed and a qualitative comparison of these solutions in terms of energy-consumption, recognition accuracy and latency is provided.
Proceedings ArticleDOI

Segmentation and tracking of interacting human body parts under occlusion and shadowing

Sangho Park, +1 more
TL;DR: The paper presents a tracking system that simultaneously segments and tracks multiple body parts of interacting people in the presence of mutual occlusion and shadow and resembles a multi-target, multi-assignment framework.
Journal ArticleDOI

The Mirror Neuron System: A Fresh View

TL;DR: The authors suggest that possibly two different “mirror” systems might underlie the development of action understanding and imitative abilities in the two cases of sensorimotor development: facial and hand movements.
References
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Proceedings ArticleDOI

Determining Optical Flow

TL;DR: In this article, a method for finding the optical flow pattern is presented which assumes that the apparent velocity of the brightness pattern varies smoothly almost everywhere in the image, and an iterative implementation is shown which successfully computes the Optical Flow for a number of synthetic image sequences.
Journal ArticleDOI

Pfinder: real-time tracking of the human body

TL;DR: Pfinder is a real-time system for tracking people and interpreting their behavior that uses a multiclass statistical model of color and shape to obtain a 2D representation of head and hands in a wide range of viewing conditions.
Journal ArticleDOI

Representation and recognition of the spatial organization of three-dimensional shapes.

TL;DR: The human visual process can be studied by examining the computational problems associated with deriving useful information from retinal images by applying the approach to the problem of representing three-dimensional shapes for the purpose of recognition.
Proceedings ArticleDOI

Recognizing human action in time-sequential images using hidden Markov model

TL;DR: The recognition rate is improved by increasing the number of people used to generate the training data, indicating the possibility of establishing a person-independent action recognizer.
Journal ArticleDOI

Visual motion perception.

TL;DR: The author uses projective relations as the theoretical foundation of his investigations of visual space and motion and concludes that during locomotion the components of the human visual environment are interpreted as rigid structures in relative motion.
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