Adaptive frame synchronization for surveillance system across a heterogeneous network

Leu, Jenq‐Shiou; Lin, Wei‐Hsiang; Tzeng, Hung-Jie; Chen, Chi-Feng; Lin, Mu-Sheng

doi:10.1016/j.engappai.2012.02.001

Cited by 7 publications

(2 citation statements)

References 20 publications

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“…Frame synchronization is often regarded as an important factor for data fusion in multi-camera systems and camera networks, and various studies have been conducted [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 ]. In many practical cases [ 14 , 15 , 16 , 17 , 18 , 19 , 20 ], such as tracking and monitoring on sports [ 14 , 15 , 16 ], human motion [ 17 , 18 ], surveillance systems [ 19 ], etc., more precise frame synchronization promises more accurate data processing results. Therefore, the evaluation of the accuracy of the frame synchronization should be carefully advanced before the endeavor to improve the quality of the synchronization itself.…”

Section: Introductionmentioning

confidence: 99%

Sub-Frame Evaluation of Frame Synchronization for Camera Network Using Linearly Oscillating Light Spot

Kim

Ishikawa

2021

Sensors

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Precisely evaluating the frame synchronization of the camera network is often required for accurate data fusion from multiple visual information. This paper presents a novel method to estimate the synchronization accuracy by using inherent visual information of linearly oscillating light spot captured in the camera images instead of using luminescence information or depending on external measurement instrument. The suggested method is compared to the conventional evaluation method to prove the feasibility. Our experiment result implies that the estimation accuracy of the frame synchronization can be achieved in sub-millisecond order.

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Section: Introductionmentioning

confidence: 99%

Sub-Frame Evaluation of Frame Synchronization for Camera Network Using Linearly Oscillating Light Spot

Kim

Ishikawa

2021

Sensors

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“…In this context, the current research presents a novel technological solution called WirelessSyncroVision (WSV), and evaluates a designed method that synchronizes the instant of the acquisition of multi-cameras with time events of a 6-DoF active marker. In the past few years, a high number of temporal alignment methods to synchronize multi-cameras have been proposed however, the large majority focused on a software approach: unmatched bandwidth of heterogeneous network environments [12], software triggering using markers [5] and the asynchronism between multiple points-of-view [4]. These methods use elaborated techniques (shape from silhouettes and volumetric analysis) [7] but results have proved that the level of temporal alignment is often insufficient in terms of accuracy for photometric evaluations [10] and 3D reconstructions [7,2].…”

Section: Introductionmentioning

confidence: 99%

WirelessSyncroVision: Wireless synchronization for industrial stereoscopic systems

Pinto

Moreira

Costa

2015

Int J Adv Manuf Technol

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The research proposes a novel technological solution for marker-based human motion capture called WirelessSyncroVision (WSV). The WSV is formed by two main modules: the visual node (WSV-V) which is based on a stereoscopic vision system and the marker node (WSV-M) that is constituted by a 6-DOF active marker. The solution synchronizes the acquisition of images in remote muti-cameras with the ON period of the active marker. This increases the robustness of the stereoscopic system to illumination changes, which is extremely relevant for programming industrial roboticarms using a human demonstrator (PbD).In addition, the research presents a robust method named Adaptive and Robust Synchronization (ARS), that is designed for temporal alignment of remote devices using a wireless network. The algorithm models the phase difference as a function of time, measuring the parameters that must be known to predict the synchronization instant between the active marker and the remote cameras.Results demonstrate that the ARS creates a balance between the real-time capability and the performance estimation of the phase difference. Therefore, this research proposes an elegant solution to synchronize image acquisition systems in real-time that is easy to implement with low operational costs however, the major advantage of the WSV is related to its high level of flexibility since it can be extended toward to other devices

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Robust global motion estimation for video security based on improved k-means clustering

Liu

et al. 2018

J Ambient Intell Human Comput

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Adaptive frame synchronization for surveillance system across a heterogeneous network

Cited by 7 publications

References 20 publications

Sub-Frame Evaluation of Frame Synchronization for Camera Network Using Linearly Oscillating Light Spot

Sub-Frame Evaluation of Frame Synchronization for Camera Network Using Linearly Oscillating Light Spot

WirelessSyncroVision: Wireless synchronization for industrial stereoscopic systems

Robust global motion estimation for video security based on improved k-means clustering

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