First Sight: A human body outline labeling system

Leung, M.K.H.; Yang, Yee‐Hong

doi:10.1109/34.385981

Cited by 154 publications

(74 citation statements)

References 26 publications

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“…Leung and Yang [63] use U-shaped edges to describe the outline of a moving human body from a video sequence. A moving edge detection technique is proposed to generate a more complete outline of the moving object, based on the difference picture and the coincidence edges which are edges of both the difference picture and the original intensity picture.…”

Section: Indirect Modelmentioning

confidence: 99%

“…However, the above mentioned feature representations do not fully capture the whole body actions. Therefore, some human modeling methods [15,39,52,[60][61][62][63][64][65][66][67][68][69][70] are also proposed to model the human body including simple blobs, 2D body modeling and 3D body modeling. Generally, the body modeling requires the 2D/3D pose estimation problem.…”

Section: Introductionmentioning

confidence: 99%

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A Review on Video-Based Human Activity Recognition

et al. 2013

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This review article surveys extensively the current progresses made toward video-based human activity recognition. Three aspects for human activity recognition are addressed including core technology, human activity recognition systems, and applications from low-level to high-level representation. In the core technology, three critical processing stages are thoroughly discussed mainly: human object segmentation, feature extraction and representation, activity detection and classification algorithms. In the human activity recognition systems, three main types are mentioned, including single person activity recognition, multiple people interaction and crowd behavior, and abnormal activity recognition. Finally the domains of applications are discussed in detail, specifically, on surveillance environments, entertainment environments and healthcare systems. Our survey, which aims to provide a comprehensive state-of-the-art review of the field, also addresses several challenges associated with these systems and applications. Moreover, in this survey, various applications are discussed in great detail, specifically, a survey on the applications in healthcare monitoring systems. OPEN ACCESSComputers 2013, 2 89

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Section: Indirect Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Review on Video-Based Human Activity Recognition

et al. 2013

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“…In the work by Leung and Yang [90] the outline of the subject is estimated as edge regions described using 2D ribbons which are U-shaped edge segments. A 2D ribbon model guides the labeling of the image data by searching for structures similar to the model.…”

Section: Indirect Model Usementioning

confidence: 99%

A Survey of Computer Vision-Based Human Motion Capture

Moeslund¹,

Granum²

2001

Computer Vision and Image Understanding

1,422

642

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“…Moreover, human motion analysis has many challenging issues, because the highly flexible structure and self-occlusion of the human body mandates complicated processes for the segmentation and analysis of motion [13]. As the human gait is known to be one of the most universal and complex of all human activities, it has been studied in medical science [9][15] [16], biomechanics [19] [20], and psychology [11] for decades.…”

Section: Introductionmentioning

confidence: 99%