297 research outputs found
Seam-guided local alignment and stitching for large parallax images
Seam-cutting methods have been proven effective in the composition step of
image stitching, especially for images with parallax. However, the
effectiveness of seam-cutting usually depends on that images can be roughly
aligned such that there exists a local region where a plausible seam can be
found. For images with large parallax, current alignment methods often fall
short of expectations. In this paper, we propose a local alignment and
stitching method guided by seam quality evaluation. First, we use existing
image alignment and seam-cutting methods to calculate an initial seam and
evaluate the quality of pixels along the seam. Then, for pixels with low
qualities, we separate their enclosing patches in the aligned images and
locally align them by extracting modified dense correspondences via SIFT flow.
Finally, we composite the aligned patches via seam-cutting and merge them into
the original aligned result to generate the final mosaic. Experiments show that
compared with the state-of-the-art seam-cutting methods, our result is more
plausible and with fewer artifacts. The code will be available at
https://github.com/tlliao/Seam-guided-local-alignment.Comment: 13 pages, 12 figures, in peer revie
Control Strategy for Improving Operation Energy Efficiency of Bow Thruster in Shipboard Microgrid
Detecting Suicidal Ideation in Chinese Microblogs with Psychological Lexicons
Suicide is among the leading causes of death in China. However, technical
approaches toward preventing suicide are challenging and remaining under
development. Recently, several actual suicidal cases were preceded by users who
posted microblogs with suicidal ideation to Sina Weibo, a Chinese social media
network akin to Twitter. It would therefore be desirable to detect suicidal
ideations from microblogs in real-time, and immediately alert appropriate
support groups, which may lead to successful prevention. In this paper, we
propose a real-time suicidal ideation detection system deployed over Weibo,
using machine learning and known psychological techniques. Currently, we have
identified 53 known suicidal cases who posted suicide notes on Weibo prior to
their deaths.We explore linguistic features of these known cases using a
psychological lexicon dictionary, and train an effective suicidal Weibo post
detection model. 6714 tagged posts and several classifiers are used to verify
the model. By combining both machine learning and psychological knowledge, SVM
classifier has the best performance of different classifiers, yielding an
F-measure of 68:3%, a Precision of 78:9%, and a Recall of 60:3%.Comment: 6 page
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