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零售業手勢姿態辨識－市場佔有率分析、產業趨勢/統計、成長預測（2025-2030）

Gesture Recognition in Retail - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2025 - 2030)
出版日期: | 出版商: Mordor Intelligence | 英文 140 Pages | 商品交期: 2-3個工作天內

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簡介目錄

零售業手勢姿態辨識市場規模預計到 2025 年為 32.6 億美元，預計到 2030 年將達到 72.3 億美元，預測期內（2025-2030 年）複合年成長率為 17.26%。

零售市場中的手勢辨識-IMG1

該市場預計將受益於全球人均收入的成長、技術進步和零售數位化的不斷發展。物聯網 (IoT) 的日益普及以及對產品消費舒適性和便利性日益成長的需求也推動了市場擴張。

根據全球改善營養聯盟預測，到 2022 年，印度食品零售店數量預計將達到約 1,300 萬家。這包括傳統商店和新商店。自 2013 年以來，它一直在持續成長，但主要是透過傳統零售商。許多零售店被認為可以為所調查的市場提供擴大的機會。人們已經創建了各種原型，以使手勢檢測比鍵盤和滑鼠等傳統介面工具更便宜。手勢越來越受到主要供應商的關注，因為它們富有表現力，易於與環境互動，並能有效地傳達訊息。

各種門禁系統​​都需要可靠的人員識別。此類系統的範例包括 ATM、筆記型電腦和行動電話。如果潛在的詐騙不符合強大、可靠的身份驗證要求，他們可能會獲得對這些系統的存取權。為了加強存取控制系統的安全性，引入了雙重認證（T-FA），它結合了兩個因素來對使用者進行身份驗證。預計這些因素將推動所研究的市場。

此外，零售商可以使用臉部辨識技術來實現更快、無摩擦的交易，透過豐富的分析來提高客戶滿意度，提供有針對性的廣告，並提高商店安全性並為 VIP 和忠誠度計畫會員提供個性化體驗。投資智慧零售技術可確保商店繼續提供最佳的店內體驗，進而提高品牌忠誠度和銷售量。

電腦視覺辨識手部動作的能力對於人機互動的未來發展至關重要。手勢多樣，具有多種意義，時空變化；人類的手是複雜的非剛性物體，難以辨識；而電腦視覺本身就是一個非姿勢問題。

COVID-19 大流行使得非接觸式通訊變得至關重要。原本被置於AR/VR和生物識別背景下的手勢姿態辨識也因此受益匪淺。如果能夠開發出獨立於平台的手勢偵測系統，將會有很大的市場發展空間。此外，隨著消費者對 AR/VR 系統越來越熟悉，並且需要與螢幕的互動最少，他們的應用可能會擴展到各個行業。智慧型手機和廣告空間現在正在協同工作，無縫地發送相關廣告並在數位領域傳遞訊息。

這是對各國將實施的眾多智慧城市計劃的回應。

零售市場手勢姿態辨識的趨勢

非接觸式技術預計將佔據主要佔有率

非接觸式技術非常節能，無需人工干預即可自動關閉，從而減少能源損失和成本。企業可以使用衛生槓桿等簡單的手動措施來保護員工免受污染表面的影響。與健康相關的費用和罰款的可能性較低，有助於抵消實施非接觸式技術所產生的成本。非接觸式科技有潛力實現並改善以便利為中心的更精簡、自主和愉快的消費者體驗。

此外，語音辨識軟體允許使用者口頭執行任務。例子包括蘋果的 Siri、谷歌的 Home 和亞馬遜的 Alexa。中小型公司開發用於商業和公共用途的語音辨識軟體，例如聲控 ATM 和火車票務機。企業可以減少輸入時間，擺脫手動記錄的束縛，並允許客戶使用聲控、免觸控設備透過語音將事件新增至日曆。

此外，非接觸式手勢姿態辨識可以根據商店扒手和辱罵顧客的資料庫對進入商店的每個人篩檢，從而識別並防止重複犯罪。一旦配備臉部辨識軟體的攝影機識別出犯罪分子並允許適當、安全地接近他們，系統就會迅速告知員工犯罪分子的身份、商店內的位置以及列入黑名單的原因。以這種方式創建已知罪犯的黑名單可以減少並消除錯誤和偏見。此策略還可以讓您的防損人員騰出時間來專注於確保客戶和員工的安全。

基於非接觸式手勢姿態辨識的 POS 系統可以快速、輕鬆地驗證客戶身份並啟用付款。與先前的生物識別技術類似，客戶無需信用卡或智慧型手機即可完成交易。手勢姿態辨識技術可用於阻止非法貿易。即使您的竊賊或智慧型手機被盜，最新的反身分技術也可以防止竊賊欺騙臉部辨識系統。該技術透過驗證鏡頭前的臉部是否為真人並與資料庫匹配來阻止假冒行為。

根據美國人口普查局預測，到2022年終，零售總額將達到約7.1兆美元，與前一年同期比較增加約5億美元。一些世界頂級零售公司的總部都位於美國，包括沃爾瑪、好市多和亞馬遜。尤其是亞馬遜，隨著電子商務在全球的擴張，收益呈現驚人的成長。如此巨大的零售額預計將推動所研究的市場。

亞太地區成長最快

根據統計和規劃實施部 (MOSPI) 的數據，印度的消費支出從 2022 年第二季的 227,981 億印度盧比（2,463.2 億美元）增至 2022 年第三季的 222,957.2 億盧比。此外，根據內務部的數據，2021年家庭平均每月在線上購買雜貨的支出超過2,300日元，而家用電子電器產品的支出略高於1,200日元。 2021年，家庭每月線上支出將接近16,000日圓。這可能是零售商實施手勢姿態辨識系統以改善客戶體驗的機會。

此外，根據全球農業資訊網路的數據，到 2022 年，印度將約有 1,300 萬家雜貨零售店。此類別包括傳統零售商和新零售商。自2013年以來，門市數量穩定成長，但大部分為傳統門市。此外，根據中國國家統計局的數據，2021年全國零售連鎖店數量為292,383家。

未來的研究應該擴展提案的技術並將其與物聯網（IoT）整合，以實現完全自動化並提高非理想條件下的手勢姿態辨識分割效能。開發了深度學習的高效虹膜影像分割技術，以提高非理想虹膜影像的分割性能，例如不同大小的虹膜、深色虹膜、眼鏡或眼瞼遮擋、光照、不合作樣本、鏡面反射等。

市場上的供應商正在開發新產品以贏得市場佔有率。例如，2022年3月，人工智慧雲端供應商百度人工智慧雲端宣布推出人工智慧手語平台，讓用戶在幾分鐘內創建用於手語翻譯和現場口譯的數位化身。作為百度人工智慧雲端數位化身平台 XiLing 推出的新產品，該平台旨在透過增加自動手語翻譯的使用來幫助殘障人士和聽力障礙 (DHH) 群體消除溝通障礙。

隨著中國經濟的成長，消費需求和生活方式、消費方式正在發生顯著變化。零售品牌和購物中心正在採用新技術，實現零售各個方面的數位化，提高整個價值鏈的效率並降低營運成本，並透過積極創新和製定提供複雜的零售服務、零售產品和零售空間。經營模式

零售業手勢姿態辨識產業概況

零售手勢姿態辨識市場較為分散。主要企業包括索尼公司、蘋果公司和谷歌公司。產品發布、高額研發支出、聯盟和收購是這些公司維持激烈競爭的主要成長策略。

2023年2月，全球全像擴增實境（「AR」）技術供應商微美全像開發了3D手勢追蹤演算法。它使用數學演算法來解碼人類手勢並透過收集目標手勢的位置並將其運動轉換為視訊畫面內的連續點的軌跡來監視使用者手勢。 3D手勢追蹤演算法是電腦視覺中的重要研究領域。該系統使用手勢、相機姿勢和位置資訊來追蹤使用者動作，這在一定程度上解決了視訊串流中的手勢追蹤問題。

2022 年 7 月，為各種電子應用領域的客戶提供服務的全球半導體先驅意法半導體宣布推出其最新的 FlightSense 飛行時間 (ToF) 多區域感測器。它與一組基本的軟體演算法相結合，描述了用於用戶檢測、手勢姿態辨識和入侵者警告的承包解決方案，特別適合 PC 市場。

其他好處

  • Excel 格式的市場預測 (ME) 表
  • 3 個月分析師支持

目錄

第1章簡介

  • 研究成果
  • 研究場所
  • 調查範圍

第2章調查方法

第3章執行摘要

第4章市場動態

  • 市場概況
  • 利用市場促進和市場約束因素
  • 市場促進因素
    • 越來越依賴手勢與機器通訊
    • 零售業更多地使用支援手勢姿態辨識的設備
  • 市場限制因素
    • 與手勢姿態辨識技術相關的演算法、數學和其他複雜性
  • 產業價值鏈分析
  • 產業吸引力－波特五力分析
    • 新進入者的威脅
    • 買家/消費者的議價能力
    • 供應商的議價能力
    • 替代品的威脅
    • 競爭公司之間的敵對關係

第5章技術概況

第6章 市場細分

  • 依技術
    • 基於觸摸的手勢姿態辨識
    • 非接觸式手勢姿態辨識
  • 按地區
    • 北美洲
    • 歐洲
    • 亞太地區
    • 拉丁美洲
    • 中東/非洲

第7章 競爭格局

  • 公司簡介
    • Apple Inc
    • Cognitec Systems GmbH
    • Crunchfish AB
    • Elliptic Labs
    • GestureTek, Inc.
    • Google LLC
    • Infineon Technologies AG
    • Intel Corporation
    • Microsoft Corporation
    • Omron Corporation
    • Sony Corporation

第8章投資分析

第9章 市場機會及未來趨勢

簡介目錄
Product Code: 50107

The Gesture Recognition in Retail Market size is estimated at USD 3.26 billion in 2025, and is expected to reach USD 7.23 billion by 2030, at a CAGR of 17.26% during the forecast period (2025-2030).

Gesture Recognition in Retail - Market - IMG1

The market will likely benefit from rising global per capita income, technological developments, and more digitization in the retail industry. The expanding use of the Internet of Things (IoT) and the growing need for comfort and convenience in product consumption are also driving market expansion.

As per the Global Alliance for Improved Nutrition, there will be around 13 million retail food stores in India by 2022. This included both conventional and new merchants within the sector. While there has been consistent growth since 2013, it has been chiefly constituted of traditional retailers. Many retail establishments would provide opportunities for the studied market to expand. Various prototypes have been created to make hand gesture detection more affordable than conventional interface tools like keyboards and mice. Hand gestures are highly expressive, easily interact with the environment, and effectively transmit information may cause leading suppliers' rising interest.

Reliable personal recognition is required by a wide variety of access control systems. Examples of these systems include ATMs, laptops, and cellular phones. If these systems fail to meet the demands of reliable and robust authentication, potential imposters may gain access to these systems. To enhance the security of access control systems, two-factor authentication (T-FA) has been introduced, wherein two factors are combined to authenticate a user. Such factors are expected to drive the studied market.

Further, retailers can use facial recognition technology to create faster and more frictionless transactions, increase customer satisfaction through rich analytics, offer targeted advertising, better manage employee attendance and store security, and personalize experiences for VIPs and loyalty program members. Investments in smart retail technology will guarantee that merchants continue giving the best in-store experience possible, improving brand loyalty and sales.

The capacity of computers to visually recognize hand movements is critical for the future development of HCI. However, vision-based recognition of hand gestures, particularly dynamic hand gestures, is a difficult interdisciplinary challenge for three reasons: hand gestures are diverse, have multiple meanings, and vary spatiotemporally; the human hand is a complex non-rigid object that is difficult to recognize; and computer vision is an ill-posed problem in and of itself.

The COVID-19 pandemic made contactless communication essential. Gesture recognition, which was relegated to AR/VR and biometric authentication background, benefited from this. The market had a lot of room for growth if platform-independent gesture detection systems were developed. Additionally, consumers' familiarity with AR/VR systems and the minimum interaction required with screens can broaden its application in various industries. Smartphones and the advertising space worked together to seamlessly transmit relevant ads and deliver information in the digital sphere.

This is in response to numerous smart city projects that would be implemented in various nations.

Gesture Recognition in Retail Market Trends

Touchless Technology is Expected to hold the Major Share

Touchless technology is more energy efficient because it shuts off automatically rather than requiring human involvement, resulting in less energy loss and cost. Simple, manual measures, such as sanitary levers, can be used by businesses to safeguard personnel from contaminated surfaces. The lower likelihood of health-related charges and fines offsets costs incurred due to deploying touchless technology. Touchless technology has the potential to enable or improve a more streamlined, self-directed, and enjoyable consumer experience, with convenience at its center.

Further, with voice recognition software, users can carry out tasks verbally. Examples include Apple's Siri, Google's Home, and Amazon's Alexa. Small businesses have created voice recognition software for commercial and public uses, like voice-activated ATMs and train ticketing devices. Businesses may reduce typing time, do away with retaining manual records, and enable customers to audibly add events to their calendars by using voice-activated, touch-free devices.

Moreover, touchless gesture recognition can identify and prevent repeat offenders by screening everyone who enters the store against a database of known shoplifters and rowdy patrons. The system quickly provides workers with the offender's identification, location within the store, and reasons for block-listing when cameras equipped with face recognition software identify offenders to ensure that the person is approached appropriately and safely. By creating this block list of known offenders, mistakes and biases are lessened and eliminated. Also, this strategy frees up loss prevention staff, allowing them to concentrate on ensuring the security of customers and employees.

Touchless-based gesture recognition point-of-sale (POS) systems can rapidly and easily verify customer identity and allow payments. Customers do not require a credit card or smartphone to complete the transaction, similar to previous biometric verification techniques. Using gesture recognition technology can help stop fraudulent transactions. The most recent anti-spoofing technology stops thieves from fooling the facial recognition system even if a user's card or smartphone is stolen. This technique prevents efforts at spoofing by ensuring that the face in front of the camera is a real person and matches the database.

According to US Census Bureau, total retail sales will have reached roughly USD 7.1 trillion by the end of 2022, an increase of approximately half a billion US dollars over the previous year. Several world's top retail corporations, such as Walmart, Costco, and Amazon, are headquartered in the United States. Amazon, in particular, has seen exceptional revenue growth in line with the global expansion of e-commerce. Such huge retail sales are expected to drive the studied market.

Asia-Pacific to Witness the Fastest Growth

According to the Ministry of Statistics and Programme Implementation (MOSPI), India's consumer spending climbed from INR 22079.81 billion ( USD 246.32 Billion) in the second quarter of 2022 to INR 22295.72 billion (USD253.07 Billion) in the third quarter. Further, According to Statistics Bureau Japan, the average monthly household spending on online food purchases in 2021 was over JPY 2.3 thousand, whereas spending on home electronics was only over JPY 1.2 thousand. In 2021, monthly household online spending was close to JPY 16,000. This may create an opportunity for retail players to deploy gesture recognition systems to enhance the customer experience.

Moreover, According to Global Agriculture Information Network, In 2022, there will be around 13 million retail grocery stores in India. Within the category, this encompassed both traditional and new retailers. While there has been a consistent number growth since 2013, it was largely made of traditional stores. Further, According to the National Bureau of Statistics of China, in 2021, there were 292,383 retail chain stores across the country.

Future studies should extend and integrate the proposed technology with the Internet of Things (IoT) to achieve full automation and increase gesture recognition segmentation performance in less-than-ideal conditions. To improve segmentation performance for non-ideal iris images, including different-sized iris, dark iris, occlusions owing to spectacles or eyelids, illumination, non-cooperative samples, and specular reflections, a high-efficiency iris image segmentation technique based on deep learning was developed.

The vendors in the market are developing new products to capture the market share. For instance, in March 2022, Baidu AI Cloud, a provider of AI clouds, unveiled an AI sign language platform capable of producing digital avatars for sign language translation and live interpretation in minutes. This platform, released as a new product of Baidu AI Cloud's digital avatar platform XiLing, promises to help break down communication barriers for the deaf and hard-of-hearing (DHH) community by increasing access to automated sign language translation.

As China's economy has grown, consumer demand and living and spending patterns have altered noticeably. Retail brands and shopping centers have continued to seize the business opportunities created by new consumption actively, not only by adopting new technologies to realize digitalization of all aspects of retail, improving the efficiency of the entire value chain, and lowering operating costs, but also by actively innovating and formulating new business models to create refined retail services, retail products, and retail space.

Gesture Recognition in Retail Industry Overview

The gesture recognition in the retail market is fragmented. Some key players are Sony Corporation, Apple Inc., and Google LLC. Product launches, high expenses on research and development, partnerships and acquisitions, etc., are the prime growth strategies these companies adopt to sustain the intense competition.

In February 2023, WiMi Hologram Cloud Inc., a global Hologram Augmented Reality ("AR") Technologies provider, created a 3D gesture tracking algorithm. This is a way of monitoring a user's gesture by collecting the target gesture's position and translating its movement into a continuous trail of points in a video frame to decode human gestures using mathematical algorithms. A three-dimensional gesture tracking algorithm is an important area of research in computer vision. The system tracks user motions using gestures, camera attitude, and position information, which somewhat helps solve the gesture-tracking problem in video streams.

In July 2022, STMicroelectronics, a global semiconductor pioneer servicing clients across various electronics applications, released its latest FlightSense Time-of-Flight (ToF) multi-zone sensor. When delivered with a suite of essential software algorithms, the combination provides a turnkey solution for user detection, gesture recognition, and intruder warning, specifically suited for the PC market.

Additional Benefits:

  • The market estimate (ME) sheet in Excel format
  • 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

  • 1.1 Study Deliverables
  • 1.2 Study Assumptions
  • 1.3 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET DYNAMICS

  • 4.1 Market Overview
  • 4.2 Introduction to Market Drivers and Restraints
  • 4.3 Market Drivers
    • 4.3.1 Increasing Dependence on Gestures to Communicate with Machines
    • 4.3.2 Increasing Use of Devices Supporting Gesture Recognition Across the Retail Sector
  • 4.4 Market Restraints
    • 4.4.1 Algorithms, Mathematical and Other Complexities Associated with the Gesture Recognition Technology
  • 4.5 Industry Value Chain Analysis
  • 4.6 Industry Attractiveness - Porter's Five Forces Analysis
    • 4.6.1 Threat of New Entrants
    • 4.6.2 Bargaining Power of Buyers/Consumers
    • 4.6.3 Bargaining Power of Suppliers
    • 4.6.4 Threat of Substitute Products
    • 4.6.5 Intensity of Competitive Rivalry

5 TECHNOLOGY SNAPSHOT

6 MARKET SEGMENTATION

  • 6.1 By Technology
    • 6.1.1 Touch-based Gesture Recognition
    • 6.1.2 Touch-less Gesture Recognition
  • 6.2 Geography
    • 6.2.1 North America
    • 6.2.2 Europe
    • 6.2.3 Asia-Pacific
    • 6.2.4 Latin America
    • 6.2.5 Middle East & Africa

7 COMPETITIVE LANDSCAPE

  • 7.1 Company Profiles
    • 7.1.1 Apple Inc
    • 7.1.2 Cognitec Systems GmbH
    • 7.1.3 Crunchfish AB
    • 7.1.4 Elliptic Labs
    • 7.1.5 GestureTek, Inc.
    • 7.1.6 Google LLC
    • 7.1.7 Infineon Technologies AG
    • 7.1.8 Intel Corporation
    • 7.1.9 Microsoft Corporation
    • 7.1.10 Omron Corporation
    • 7.1.11 Sony Corporation

8 INVESTMENT ANALYSIS

9 MARKET OPPORTUNITIES AND FUTURE TRENDS