Proceedings ArticleDOI
Fisheye camera modeling for human segmentation refinement in indoor videos
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The constructed camera model is utilized to achieve a simple geometric reasoning that corrects gaps and mistakes of the human figure segmentation, and enables the inference of possible real world positions of a segmented cluster of pixels in the video frame.Abstract:
In this paper, we concentrate on refining the results of segmenting human presence from indoors videos acquired by a fisheye camera, using a 3D mathematical model of the camera. The model has been calibrated according to the specific indoor environment that is being monitored. Human segmentation is implemented using a standard established technique. The fisheye camera used for video acquisition is modeled using a spherical element, while the parameters of the camera model are determined only once, using the correspondence of a number of user-defined landmarks, both in real world coordinates and on the acquired video frame. Subsequently, each pixel of the video frame is inversely mapped to the direction of view in the real world and the relevant data are stored in look-up tables for very fast utilization in real-time video processing. The proposed fisheye camera model enables the inference of possible real world positions of a segmented cluster of pixels in the video frame. In this work, we utilize the constructed camera model to achieve a simple geometric reasoning that corrects gaps and mistakes of the human figure segmentation. Initial results are also presented for a small number of video sequences, which prove the efficiency of the proposed method.read more
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Journal ArticleDOI
Refinement of human silhouette segmentation in omni-directional indoor videos☆
TL;DR: The proposed calibrated camera model is utilized to achieve a simple geometric reasoning that corrects gaps and mistakes of the human figure segmentation, detects segmented human silhouettes inside and outside the room and rejects segmentation that corresponds to non-human activity.
Journal ArticleDOI
A deep survey on supervised learning based human detection and activity classification methods
TL;DR: This paper reviews the automatic human detection and their activity recognition in the video sequences and static images and special emphasis have been given on convolution neural network that solves the problem of human segmentation, efficient classification and activity recognition.
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Pose recognition in indoor environments using a fisheye camera and a parametric human model
TL;DR: A system that uses computer vision techniques and a deformable 3D human model, in order to recognize the posture of a monitored person, given the segmented human silhouette from the background, is presented.
Proceedings ArticleDOI
Human centered computing for the development of assistive environments: the STHENOS project
TL;DR: The research conducted within the framework of the STHENOS project aims at the development of methodologies and tools to compose pervasive human-centered systems, which will be able to understand the human state in assistive environments using audiovisual and biological signals.
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Environment Mapping and Other Applications of World Projections
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