Proceedings ArticleDOI
Human motion analysis: a review
Jake K. Aggarwal,Qin Cai +1 more
- pp 90-102
Reads0
Chats0
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.read more
Citations
More filters
Journal ArticleDOI
Gait recognition using image self-similarity
TL;DR: It is argued that the similarity plot encodes a projection of gait dynamics, which is also correspondence-free, robust to segmentation noise, and works well with low-resolution video.
Journal ArticleDOI
3D Articulated Models and Multiview Tracking with Physical Forces
TL;DR: A fast recursive algorithm is used to solve the dynamical equations of motion of any 3D articulated model using physical forces applied to each rigid part of a kinematic 3D model of the object the authors are tracking.
Patent
Gesture personalization and profile roaming
TL;DR: In this paper, a gesture-based system may have default or pre-packaged gesture information, where a gesture is derived from a user's position or motion in a physical space.
Posted Content
RGB-D-based Human Motion Recognition with Deep Learning: A Survey
TL;DR: A detailed overview of recent advances in RGB-D-based motion recognition is presented in this paper, where the reviewed methods are broadly categorized into four groups, depending on the modality adopted for recognition: RGB-based, depth based, skeleton-based and RGB+D based.
Journal ArticleDOI
Integration of Vision and Inertial Sensors for 3D Arm Motion Tracking in Home-based Rehabilitation
Yaqin Tao,Huosheng Hu,Huiyu Zhou +2 more
TL;DR: A real-time hybrid solution to articulated 3D arm motion tracking for home-based rehabilitation by combining visual and inertial sensors is introduced and compared with commercial marker-based systems, CODA and Qualysis.
References
More filters
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.
David Marr,H. K. Nishihara +1 more
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
Junji Yamato,J. Ohya,K. Ishii +2 more
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.