Adaptive detection and localization of moving objects in image sequences

1999 ◽  
Vol 14 (4) ◽  
pp. 277-296 ◽  
Author(s):  
N. Paragios ◽  
G. Tziritas
Author(s):  
Hiroyuki Uchiyama ◽  
Daisuke Deguchi ◽  
Tomokazu Takahashi ◽  
Ichiro Ide ◽  
Hiroshi Murase

Author(s):  
S. Gao ◽  
Z. Ye ◽  
C. Wei ◽  
X. Liu ◽  
X. Tong

<p><strong>Abstract.</strong> The high-speed videogrammetric measurement system, which provides a convenient way to capture three-dimensional (3D) dynamic response of moving objects, has been widely used in various applications due to its remarkable advantages including non-contact, flexibility and high precision. This paper presents a distributed high-speed videogrammetric measurement system suitable for monitoring of large-scale structures. The overall framework consists of hardware and software two parts, namely observation network construction and data processing. The core component of the observation network is high-speed cameras to provide multiview image sequences. The data processing part automatically obtains the 3D structural deformations of the key points from the captured image sequences. A distributed parallel processing framework is adopted to speed up the image sequence processing. An empirical experiment was conducted to measure the dynamics of a double-tube five-layer building structure on the shaking table using the presented videogrammetric measurement system. Compared with the high-accuracy total station measurement, the presented system can achieve a sub-millimeter level of coordinates discrepancy. The 3D deformation results demonstrate the potential of the non-contact high-speed videogrammetric measurement system in dynamic monitoring of large-scale shake table tests.</p>


2008 ◽  
Vol 25 (4) ◽  
pp. 309-323 ◽  
Author(s):  
José Luis Crespo ◽  
Marta Zorrilla ◽  
Pilar Bernardos ◽  
Eduardo Mora

1997 ◽  
Vol 07 (04) ◽  
pp. 283-299
Author(s):  
Jae-Ho Choi ◽  
Bong-Tae Kim ◽  
Won-Koo Kim

A motion vector selective moving object estimation algorithm that preserves the exact shapes and textures of moving objects is presented. In order to extract multiple moving objects with arbitrary motion vectors embedded in the sequence of image frames of cluttered stationary background as alleviating the aliasing effects, both 3D spectral filter banks, called velocity-tuned filter banks, and time-recursive Kalman filter are incorporated to work in parallel. Furthermore, using the fact that the motion energy for each one of the moving objects takes a unique part of the spectrum in the 3D spatio-temporal frequency space, the rotation invariant multiple moving objects detection is also possible when using the proposed filter banks. Simulations have been run to analyze the performance of our filtering algorithm utilizing image sequences of natural scenes. The accurate and robust sets of estimation results are observed down to signal-to-noise ratios of 12 dB.


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