肉身
发表于 2025-3-25 04:34:39
Simulating Human Activities for Synthetic Inputs to Sensor Systems which permits the authoring of functional crowds of people going about role-, context-, and schedule-dependent activities. The capabilities and authoring tools for these functional crowd simulations are described with the intention of readily creating ground truth data for distributed sensor system design and evaluation.
Femish
发表于 2025-3-25 07:57:13
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Cholagogue
发表于 2025-3-25 11:38:52
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MAUVE
发表于 2025-3-25 16:46:40
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琐碎
发表于 2025-3-25 22:09:54
J. Scott Keltie (Assistant Secretary)tion, object appearance measurement is employed to validate the labeling results. Experimental results demonstrate the performance of our approach on real video sequences for cameras with overlapping and non-overlapping views.
Encephalitis
发表于 2025-3-26 02:43:26
A Comparison of Techniques for Camera Selection and Hand-Off in a Video Network experimental comparison using centralized and distributed computational models. We provide simulation and experimental results using real data for various scenarios of a large number of cameras and objects for in-depth understanding of strengths and weaknesses of these techniques.
Femine
发表于 2025-3-26 06:09:24
Distributed Sensing and Processing for Multi-Camera Networksand parallelized implementations of popular tools used for statistical inference in non-linear systems, of which multi-camera systems are examples. Finally, we highlight the use of the emerging theory of compressive sensing in reducing the amount of data sensed and communicated by a camera network.
坦白
发表于 2025-3-26 10:34:49
Tracking of Multiple Objects over Camera Networks with Overlapping and Non-overlapping Viewstion, object appearance measurement is employed to validate the labeling results. Experimental results demonstrate the performance of our approach on real video sequences for cameras with overlapping and non-overlapping views.
FILLY
发表于 2025-3-26 16:14:52
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oracle
发表于 2025-3-26 20:18:23
https://doi.org/10.1057/9780230253223n computer vision. Robust cognitive visual tracking algorithms facilitate answering important questions regarding how objects move and interact in complex environments. They have broad applications including surveillance, navigation, human computer interfaces, object recognition, motion analysis and video indexing, to name a few.