Acquiring 3D models of non-rigid moving objects from time and viewpoint varying image sequences: a step toward left ventricle recovery

1997 ◽  
Vol 19 (3) ◽  
pp. 253-259 ◽  
Author(s):  
Y. Sato ◽  
M. Moriyama ◽  
M. Hanayama ◽  
H. Naito ◽  
S. Tamura
Keyword(s):  
Left Ventricle ◽  
Moving Objects ◽  
3D Models ◽  
Image Sequences

scholarly journals Cascaded Regression-Based Segmentation of Cardiac CT under Probabilistic Correspondences

2020 ◽  
Vol 10 (14) ◽  
pp. 4947
Author(s):  
Jang Pyo Bae ◽  
Malinda Vania ◽  
Siyeop Yoon ◽  
Sojeong Cheon ◽  
Chang Hwan Yoon ◽  
...  
Keyword(s):  
Left Ventricle ◽  
Left Atrium ◽  
Cardiac Ct ◽  
Computation Time ◽  
3D Models ◽  
Active Appearance Models ◽  
Point Correspondence ◽  
Construction Methods ◽  
Ct Segmentation ◽  
Cascaded Regression

The creation of 3D models for cardiac mapping systems is time-consuming, and the models suffer from issues with repeatability among operators. The present study aimed to construct a double-shaped model composed of the left ventricle and left atrium. We developed cascaded-regression-based segmentation software with probabilistic point and appearance correspondence. Group-wise registration of point sets constructs the point correspondence from probabilistic matches, and the proposed method also calculates appearance correspondence from these probabilistic matches. Final point correspondence of group-wise registration constructed independently for three surfaces of the double-shaped model. Stochastic appearance selection of cascaded regression enables the effective construction in the aspect of memory usage and computation time. The two correspondence construction methods of active appearance models were compared in terms of the paired segmentation of the left atrium (LA) and left ventricle (LV). The proposed method segmented 35 cardiac CTs in six-fold cross-validation, and the symmetric surface distance (SSD), Hausdorff distance (HD), and Dice coefficient (DC), were used for evaluation. The proposed method produced 1.88 ± 0.37 mm of LV SSD, 2.25 ± 0.51 mm* of LA SSD, and 2.06 ± 0.34 mm* of the left heart (LH) SSD. Additionally, DC was 80.45% ± 4.27%***, where * p < 0.05, ** p < 0.01, and *** p < 0.001. All p values derive from paired t-tests comparing iterative closest registration with the proposed method. In conclusion, the authors developed a cascaded regression framework for 3D cardiac CT segmentation.

Removal of Moving Objects from a Street-View Image by Fusing Multiple Image Sequences

2010 ◽  
Author(s):  
Hiroyuki Uchiyama ◽  
Daisuke Deguchi ◽  
Tomokazu Takahashi ◽  
Ichiro Ide ◽  
Hiroshi Murase
Keyword(s):  
Moving Objects ◽  
Image Sequences ◽  
Multiple Image ◽  
Street View

scholarly journals DEVELOPMENT OF A HIGH-SPEED VIDEOGRAMMETRIC MEASUREMENT SYSTEM WITH APPLICATION IN LARGE-SCALE SHAKING TABLE TEST

2019 ◽  
Vol IV-2/W7 ◽  
pp. 33-38
Author(s):  
S. Gao ◽  
Z. Ye ◽  
C. Wei ◽  
X. Liu ◽  
X. Tong
Keyword(s):  
Data Processing ◽  
Measurement System ◽  
High Speed ◽  
Large Scale ◽  
Moving Objects ◽  
Shaking Table Test ◽  
Image Sequences ◽  
Shaking Table ◽  
Dynamic Monitoring ◽  
Observation Network

<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>

Moving objects forecast in image sequences using autoregressive algorithms

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

Time-Variant Moving Objects Extraction using Velocity-Tuned Filter Banks and Time-Recursion Method in Infrared Image Sequences

1997 ◽  
Vol 07 (04) ◽  
pp. 283-299
Author(s):  
Jae-Ho Choi ◽  
Bong-Tae Kim ◽  
Won-Koo Kim
Keyword(s):  
Moving Objects ◽  
Filter Banks ◽  
Temporal Frequency ◽  
Motion Vector ◽  
Infrared Image ◽  
Estimation Algorithm ◽  
Image Sequences ◽  
Natural Scenes ◽  
Recursion Method ◽  
Frequency Space

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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