Love the Way You Walk

迷戀你的步伐

Listen carefully to the footsteps in the family home, especially if it has wooden floors unmuffled by carpets, and you can probably work out who it is that is walking about. The features most commonly used to identify people are faces, voices, finger prints and retinal scans. But their “behavioural biometrics”, such as the way they walk, are also giveaways.

仔細聽家里的腳步聲，特別是家里鋪的是木地板而又沒有地毯消聲的話，你大概可以辨認出是誰在走動。最常用于身份識別的體征是面容、聲音、指紋和視網膜掃描。但步態等“生物行為特征”也是可循之跡。

Researchers have, for several years, used video cameras and computers to analyse people’s gaits, and are now quite good at it. But translating such knowledge into a practical identification system can be tricky – especially if that system is supposed to be covert. Cameras are often visible, are fiddly to set up, require good lighting and may have their view obscured by other people. So a team led by Krikor Ozanyan of the University of Manchester, in England and Patricia Scully of the National University of Ireland, in Galway have been looking for a better way to recognise gait. Their answer: pressure-sensitive mats.

近年來，研究人員一直在用攝像機和計算機分析人的步態，目前技術已經相當成熟。但要將這些知識轉化為實用的識別系統并不容易，尤其是還需要實現隱蔽性。攝像機往往容易被看到，安裝也較為繁瑣，又需要有足夠的光線，而且鏡頭還可能被他人遮擋。因此，英國曼徹斯特大學的克里科爾·奧贊揚(Krikor Ozanyan)和愛爾蘭國立大學戈爾韋的帕特麗夏·斯高莉(Patricia Scully)帶領的團隊一直在探索更好的識別步態的方法。他們的解決方案是使用壓敏墊。

In themselves, such mats are nothing new. They have been part of security systems for donkeys’ years. But Dr Ozanyan and Dr Scully use a sophisticated version that can record the amount of pressure applied in different places as someone walks across it. These measurements form a pattern unique to the walker. Dr Ozanyan and Dr Scully therefore turned, as is now commonplace for anything to do with pattern recognition, to an artificial-intelligence system that uses machine learning to disentangle and recognise such patterns.

壓敏墊本身并不是什么新發明，長久以來一直是安保系統的一部分。但奧贊揚和斯高莉使用的是更精密的壓敏墊，可以在有人走過時記錄步伐在不同位置產生的壓力值。這些測量數據構成了步行者獨有的步態模式。于是，兩位研究人員按照如今識別模式的普遍做法，把數據輸入一套人工智能系統，運用機器學習來梳理并識別這些模式。

It seems to work. In a study published earlier this year the two researchers tested their system on a database of footsteps trodden by 127 different people. They found that its error rate in identifying who was who was a mere 0.7%. And Dr Scully says that even without a database of footsteps to work with the system can determine someone’s sex (women and men, with wide and narrow pelvises respectively, walk in different ways) and guess, with reasonable accuracy, a subject’s age.

這看來行得通。在今年早前發表的一項研究中，兩位研究人員運用127人的足跡數據測試了該系統。他們發現，系統識別身份的錯誤率僅為0.7%。斯高莉說，即使不搭配使用足跡數據庫，系統也能確定受試者的性別(女性骨盆寬，男性骨盆窄，因而行走方式不同)，并可以還算準確地估計出其年齡。

A mat-based gait-recognition system has the advantage that it would work in any lighting conditions – even pitch-darkness. And though it might fail to identify someone if, say, she was wearing stilettos and had been entered into the database while wearing trainers, it would be very hard to fool it by mimicking the gait of an individual who was allowed admission to a particular place.

壓敏墊步態識別系統的優點是可以在任何光照條件下工作，即使一片漆黑也沒問題。如果數據庫之前輸入的是某人穿運動鞋時的步態，當她換成穿高跟鞋走路時，系統可能就無法識別了。但是，如果想模仿某人的步態來欺騙系統以獲準進入特定地點會非常困難。

The latest phase of Dr Ozanyan’s and Dr Scully’s project is a redesign of the mat. The old mats contained arrays of individual pressure sensors. The new ones contain grids of optical fibres. Light-emitting diodes distributed along two adjoining edges of a mat transmit light into the fibres. Sensors on the opposite edges (and thus the opposite ends of the optical fibres) measure how much of that light is received. Any pressure applied to part of the mat causes a distortion in the fibres and a consequent change in the amount of light transmitted. Both the location and amount of change can be plotted and analysed by the machine-learning system.

奧贊揚和斯高莉的研究項目的最新進展是經過重新設計的壓敏墊。原來的墊子包含由單個壓力傳感器組成的陣列。新的墊子則包含多組光纖網格。分布在墊子相鄰兩條邊上的發光二極管將光傳輸到光纖中。安裝在對面兩條邊上(也就是光纖的另一端)的傳感器測量接收到的光量。施加到墊子上某處的任何壓力都會引起光纖變形，進而導致傳輸光量的變化。機器學習系統可以識別并分析變化發生的位置和變化的量。

Dr Ozanyan says that the team have built a demonstration fibre-optic mat, two metres long and a metre wide, using materials that cost £100 ($130). They are now talking to companies about commercialising it. One application might be in health care, particularly for the elderly. A fibre-optic mat installed in a nursing home or an old person’s own residence could monitor changes in an individual’s gait that presage certain illnesses. That would provide early warning of someone being at greater risk of falling over, say, or of their cognition becoming impaired.

奧贊揚說，該團隊已制成了一塊兩米長、一米寬的演示用光纖墊，材料成本為100英鎊(130美元)。他們正與多家公司洽談，希望將其商業化。醫療保健或許會是應用領域之一，特別是在照護老年人方面。將光纖墊安裝在養老院或老人自己家中，可以監測一個人步態的變化，預測某些疾病。這將提供早期預警，例如提醒某人較有可能摔倒或出現認知受損。

Gait analysis might also be used as a security measure in the workplace, monitoring access to restricted areas, such as parts of military bases, server farms or laboratories dealing with hazardous materials. In these cases, employees would need to agree to their gaits being scanned, just as they would agree to the scanning of their faces or retinas for optical security systems.

步態分析也可作為工作場所的安保措施，用于監控限制區域的人員進出，例如軍事基地、服務器農場，或處理危險品的實驗室。在這些情況下，員工需要同意系統掃描自己的步態，就像同意光學安保系統掃描自己的面部或視網膜那樣。

Perhaps the most intriguing use of gait-recognition mats, though, would be in public places, such as airports. For that to work, the footsteps of those to be recognised would need to have been stored in a database, which would be harder to arrange than the collection of mugshots and fingerprints that existing airport security systems rely on. Some people, however, might volunteer for it. Many aircrew or preregistered frequent flyers would welcome anything that speeded up one of the most tiresome parts of modern travel.

不過，步態識別墊最吸引人的用途可能在公共場所，例如機場。要實現這一點，被識別者的步態資料需要被提前存儲到數據庫中，而這會比機場現有安全系統所倚賴的面部照片和指紋更難收集。但有些人可能會自愿提供。任何革新，若能加速安檢這一現代出行中最煩人的環節之一，許多空勤人員或預先登記的飛行常客都會歡迎它。

環球網校友情提示：以上內容是英語翻譯資格頻道為您整理的2020上半年翻譯資格考試一級筆譯考試精選習題六，點擊下面按鈕免費下載更多精品備考資料。