我司以停產(chǎn)控制系統(tǒng)零部件、為領(lǐng)先優(yōu)勢(shì)、我們有大量庫存和盈余操縱系統(tǒng)零件、停產(chǎn)的控制系統(tǒng)部分硬件、我們也發(fā)布了許多的硬件和產(chǎn)品來支持你現(xiàn)有的控制系統(tǒng)或運(yùn)用最新的控制技術(shù)、停產(chǎn)的“DCS系統(tǒng)備品 備件 PLC模塊 備件”整機(jī)及配件系列、有著強(qiáng)大的優(yōu)勢(shì)只要您需要的PLC產(chǎn)品、我們就能幫您找到。公司以“專業(yè)、 誠信、創(chuàng)新、合作、共贏”的經(jīng)營理念、不斷開發(fā)新產(chǎn)品、為客戶提供優(yōu)質(zhì)服務(wù)、以最大限度追求客戶滿意度、并不斷開拓新領(lǐng)域業(yè)務(wù),充足庫存，交貨期快，
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Many smartphone apps allow users to transform into animals, swap faces with other people, and much more. Now, such technological distractions look set to become even more dazzling, as Imperial College researchers have created the most advanced technique yet for building digitized 3D facial models – and it has a vast array of other potential uses.
When computers process faces, they typically rely on a 3D morphable model (3DMM), which represents an average face, but also contains information on common patterns of deviation from that average — such as length of face — and how they impact other facial features. Based on these common correlations, a computer then characterizes faces — not based on every point in a 3D scan, but by mere consideration of the basic ways in which an individual's face deviates from the average.
However, to account for all the ways faces can vary, 3DMMs must integrate information on a large number of faces, which necessitates scanning lots of people and then labeling all their features. By definition, this is an extremely time consuming process, and consequently even the current best models are based on only a few hundred individuals, and have limited ability to model people of different ages and races — as FaceApp users found in April, 3DMMs often have a bias towards white people.
Snapchat shots collage Photo: sputniknews.com
Now, a team of researchers at Imperial College London, led by computer scientist James Booth, have developed a new method, capable of automating 3DMM construction and incorporating a wider spectrum of humanity into its memory bank.
The method depends on three major steps — first an algorithm automatically landmarks facial scans, labeling the tip of the nose and other points, then another algorithm lines up all scans according to their landmarks and combines them into a model, and finally an algorithm identifies and removes any poor scans.
Booth and colleagues also applied their method to a set of almost 10,000 demographically diverse facial scans, conducted at London's renowned Science Museum by plastic surgeons who endeavor to improve reconstructive surgery. Applying the algorithm to those scans created a "large scale facial model" (LSFM).
Tests demonstrated the team's LSFM much more accurately represented faces when pitted against other applications. In one comparison, models of a child's face were created using a photograph — every other popular morphable provision struggled to emulate a child's looks, while the LSFM almost perfectly recreated them.
Booth's application was also able to create specific morphable models for different races and ages, and to intuitively classify individuals into particular demographic groups. Booth's team has already put the new model to work.
（DCS系統(tǒng)）和（機(jī)器人系統(tǒng)）及（大型伺服控制系統(tǒng)）備件大賣！叫賣！特賣！賣賣賣！
