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市場調查報告書
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1444610

零售業手勢辨識 - 市場佔有率分析、產業趨勢與統計、成長預測（2024 - 2029 年）

Gesture Recognition in Retail - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2024 - 2029)
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

零售市場手勢辨識市場規模預計到 2024 年為 27.8 億美元，預計到 2029 年將達到 61.6 億美元，在預測期內（2024-2029 年）CAGR為 17.26%。

零售業中的手勢辨識 - 市場

該市場可能會受益於全球人均收入的成長、技術的發展以及零售業的數位化程度的提高。物聯網 (IoT) 的廣泛使用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的數據，到 2022 年，印度將有約 1,300 萬家食品零售店。其中包括該行業的傳統商家和新商家。雖然自 2013 年以來一直持續成長，但主要由傳統零售商組成。許多零售機構將為所研究的市場提供擴展的機會。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。手勢表現力強，易於與環境互動，有效傳遞訊息，可能會引起領先供應商的興趣上升。

各種門禁系統​​都需要可靠的個人識別。這些系統的範例包括 ATM、筆記型電腦和蜂窩電話。如果這些系統無法滿足可靠和穩健的身份驗證的要求，潛在的冒名頂替者可能會獲得這些系統的存取權限。為了增強存取控制系統的安全性，引入了雙重認證（T-FA），其中組合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創建更快、更順暢的交易，透過豐富的分析來提高客戶滿意度，提供有針對性的廣告，更好地管理員工出勤和商店安全，並為VIP 和忠誠度計畫會員提供個人化體驗。對智慧零售技術的投資將保證商家持續提供最佳的店內體驗，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。然而，基於視覺的手勢識別，特別是動態手勢，是一項艱鉅的跨學科課題，原因有三個：手勢是多種多樣的，具有多種含義，並且時空變化；人手是個複雜的非剛性物體，難以辨識；電腦視覺本身就是一個不適定問題。

COVID-19 大流行使得非接觸式通訊變得至關重要。原本屬於AR/VR和生物辨識認證背景的手勢辨識則受益於此。如果開發出獨立於平台的手勢偵測系統，市場還有很大的成長空間。此外，消費者對AR/VR系統的熟悉度以及與螢幕所需的最少互動可以拓寬其在各行業的應用。智慧型手機和廣告空間協同工作，無縫傳輸相關廣告並在數位領域傳遞訊息。

這是對將在各國實施的眾多智慧城市計畫的回應。

零售市場趨勢中的手勢識別

Touchless Technology預計將持有主要股份

非接觸式技術更節能，因為它會自動關閉而不需要人工參與，從而減少能源損失和成本。企業可以使用簡單的手動措施（例如衛生槓桿）來保護人員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，抵消了部署非接觸式技術所產生的成本。非接觸式科技有潛力實現或改善更精簡、自主和愉快的消費者體驗，其核心是便利性。

此外，透過語音辨識軟體，使用者可以口頭執行任務。例子包括蘋果的 Siri、谷歌的 Home 和亞馬遜的 Alexa。小型企業已經創建了用於商業和公共用途的語音辨識軟體，例如聲控 ATM 和火車票務設備。企業可以減少打字時間，取消保留手動記錄，並使客戶能夠透過使用語音啟動的非接觸式設備以聲音方式將事件添加到他們的日曆中。

此外，非接觸式手勢識別可以根據已知的商店扒手和吵鬧顧客的資料庫對進入商店的每個人進行篩選，從而識別並防止重複犯罪。當配備人臉辨識軟體的攝影機識別出違法者時，該系統會快速向工作人員提供違法者的身份、店內位置以及屏蔽原因，以確保適當且安全地接近該人。透過建立已知違規者的黑名單，可以減少和消除錯誤和偏見。此外，該策略還解放了防損人員，使他們能夠專注於確保客戶和員工的安全。

基於非接觸式手勢識別的銷售點 (POS) 系統可以快速、輕鬆地驗證客戶身份並允許付款。與先前的生物辨識技術類似，客戶不需要信用卡或智慧型手機即可完成交易。使用手勢識別技術可以幫助阻止詐騙交易。即使用戶的卡片或智慧型手機被盜，最新的反欺騙技術也能阻止竊賊欺騙臉部辨識系統。該技術透過確保鏡頭前的臉部是真人並且與資料庫匹配來防止欺騙行為。

根據美國人口普查局的數據，到2022年底，零售總額將達到約7.1兆美元，比前一年增加約5億美元。沃爾瑪、好市多、亞馬遜等幾家世界頂尖零售公司的總部都位於美國。尤其是亞馬遜，隨著電子商務的全球擴張，收入出現了驚人的成長。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

根據統計和計畫實施部 (MOSPI) 的數據，印度消費者支出從 2022 年第二季的 220798.1 億印度盧比（2,463.2 億美元）攀升至第三季的 222957.2 億印度盧比（2,530.7 億美元）。此外，根據日本統計局的數據，2021年家庭平均每月在線上購買食品的支出超過2,300日元，而家用電子產品的支出僅超過1,200日元。 2021年，家庭每月線上支出接近16,000日圓。這可能為零售企業創造機會部署手勢識別系統以增強客戶體驗。

此外，根據全球農業資訊網預測，到2022年，印度將有約1,300萬家零售雜貨店。在該類別中，這包括傳統零售商和新零售商。儘管自 2013 年以來數量持續成長，但主要由傳統商店組成。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所提出的技術並將其與物聯網（IoT）整合，以實現完全自動化並提高在不太理想的條件下的手勢識別分割性能。為了提高非理想虹膜影像的分割性能，包括不同尺寸虹膜、深色虹膜、眼鏡或眼瞼遮擋、照明、非合作樣本和鏡面反射等，提出一種基於深度學習的高效虹膜影像分割技術發展了。

市場上的供應商正在開發新產品以佔領市場佔有率。例如，2022年3月，人工智慧雲端供應商百度人工智慧雲端推出了人工智慧手語平台，能夠在幾分鐘內產生用於手語翻譯和現場口譯的數位化身。該平台作為百度人工智慧雲端數位化身平台西靈的新產品發布，承諾透過增加自動手語翻譯的機會來幫助聾啞和聽力障礙（DHH）社群打破溝通障礙。

隨著中國經濟的發展，消費者的需求以及生活和消費模式發生了顯著變化。零售品牌和購物中心持續積極抓住新消費創造的商機，不僅採用新技術實現零售各環節數位化，提升全價值鏈效率、降低營運成本，積極創新和製定新商業模式，打造精細化零售服務、零售產品、零售空間。

零售業手勢辨識概述

零售市場的手勢辨識是碎片化的。一些主要參與者包括索尼公司、蘋果公司和谷歌公司。產品發布、高額研發費用、合作和收購等是這些公司為維持激烈競爭而採取的主要成長策略。

2023年2月，全球全像擴增實境（「AR」）技術供應商微美全像創造了3D手勢追蹤演算法。這是一種監視使用者手勢的方法，透過收集目標手勢的位置並將其運動轉換為視訊畫面中的連續點軌跡，以使用數學演算法解碼人類手勢。3D手勢追蹤演算法是電腦視覺研究的一個重要領域。該系統使用手勢、攝影機姿態和位置資訊來追蹤使用者動作，這在一定程度上有助於解決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發布了最新的 FlightSense 飛行時間 (ToF) 多區域感測器。當與一套基本軟體演算法一起交付時，該組合可為用戶檢測、手勢識別和入侵者警告提供交鑰匙解決方案，特別適合 PC 市場。

額外的好處：

  • Excel 格式的市場估算 (ME) 表
  • 3 個月的分析師支持

目錄

第 1 章：簡介

  • 研究成果
  • 研究假設
  • 研究範圍

第 2 章：研究方法

第 3 章：執行摘要

第 4 章：市場動態

  • 市場概況
  • 市場促進因素與限制簡介
  • 市場促進因素
    • 與機器交流越來越依賴手勢
    • 零售業擴大使用支援手勢識別的設備
  • 市場限制
    • 與手勢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
    • 替代產品的威脅
    • 競爭激烈程度

第 5 章：技術概覽

第 6 章：市場區隔

  • 依技術
    • 基於觸摸的手勢識別
    • 非接觸式手勢識別
  • 地理
    • 北美洲
    • 歐洲
    • 亞太
    • 拉丁美洲
    • 中東和非洲

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：市場機會與未來趨勢

簡介目錄
Product Code: 50107

The Gesture Recognition in Retail Market size is estimated at USD 2.78 billion in 2024, and is expected to reach USD 6.16 billion by 2029, growing at a CAGR of 17.26% during the forecast period (2024-2029).

Gesture Recognition in Retail - Market

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