Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
We present a novel templateless approach for nonrigid reconstruction and motion tracking using a single RGB-D camera. Without any template prior, our system achieves accurate reconstruction and tracking for considerably deformable objects. To robustly register the input sequence of partial depth scans with dynamic motion, we propose an efficient local-to-global hierarchical optimization framework inspired by the idea of traditional structure-from-motion. Our proposed framework mainly consists of two stages, local nonrigid bundle adjustment and global optimization. To eliminate error accumulation during the nonrigid registration of loop motion sequences, we split the full sequence into several segments and apply local nonrigid bundle adjustment to align each segment locally. Global optimization is then adopted to combine all segments and handle the drift problem through loop-closure constraint. By fitting to the input partial data, a deforming 3D model sequence of dynamic objects is finally generated. Experiments on both synthetic and real test data sets and comparisons with state of the art demonstrate that our approach can handle considerable motions robustly and efficiently, and reconstruct high-quality 3D model sequences without drift.
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Source |
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http://dx.doi.org/10.1109/TIP.2017.2740624 | DOI Listing |
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