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市场调查报告书
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1444610

零售业手势辨识 - 市场占有率分析、产业趋势与统计、成长预测（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个工作天内

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简介目录

零售市场手势辨识市场规模预计到 2024 年为 27.8 亿美元，预计到 2029 年将达到 61.6 亿美元，在预测期内（2024-2029 年）CAGR为 17.26%。

零售业中的手势辨识 - 市场

该市场可能会受益于全球人均收入的成长、技术的发展以及零售业的数位化程度的提高。物联网 (IoT) 的广泛使用以及对产品消费舒适性和便利性日益增长的需求也推动了市场扩张。

根据全球改善营养联盟的数据，到 2022 年，印度将有约 1,300 万家食品零售店。其中包括该行业的传统商家和新商家。虽然自 2013 年以来一直持续成长，但主要由传统零售商组成。许多零售机构将为所研究的市场提供扩展的机会。人们已经创建了各种原型，以使手势检测比键盘和滑鼠等传统介面工具更便宜。手势表现力强，易于与环境互动，有效传递讯息，可能会引起领先供应商的兴趣上升。

各种门禁系统​​都需要可靠的个人识别。这些系统的范例包括 ATM、笔记型电脑和蜂窝电话。如果这些系统无法满足可靠和稳健的身份验证的要求，潜在的冒名顶替者可能会获得这些系统的存取权限。为了增强存取控制系统的安全性，引入了双重认证（T-FA），其中组合两个因素来对使用者进行身份验证。预计这些因素将推动所研究的市场。

此外，零售商可以使用脸部辨识技术来创建更快、更顺畅的交易，透过丰富的分析来提高客户满意度，提供有针对性的广告，更好地管理员工出勤和商店安全，并为VIP 和忠诚度计画会员提供个人化体验。对智慧零售技术的投资将保证商家持续提供最佳的店内体验，提高品牌忠诚度和销售量。

电脑视觉辨识手部动作的能力对于人机互动的未来发展至关重要。然而，基于视觉的手势识别，特别是动态手势，是一项艰鉅的跨学科挑战，原因有三个：手势是多种多样的，具有多种含义，并且时空变化；人手是个复杂的非刚性物体，难以辨识；电脑视觉本身就是一个不适定问题。

COVID-19 大流行使得非接触式通讯变得至关重要。原本属于AR/VR和生物辨识认证背景的手势辨识则受益于此。如果开发出独立于平台的手势侦测系统，市场还有很大的成长空间。此外，消费者对AR/VR系统的熟悉度以及与萤幕所需的最少互动可以拓宽其在各行业的应用。智慧型手机和广告空间协同工作，无缝传输相关广告并在数位领域传递讯息。

这是对将在各国实施的众多智慧城市计画的回应。

零售市场趋势中的手势识别

Touchless Technology预计将持有主要股份

非接触式技术更节能，因为它会自动关闭而不需要人工参与，从而减少能源损失和成本。企业可以使用简单的手动措施（例如卫生槓桿）来保护人员免受污染表面的影响。与健康相关的费用和罚款的可能性较低，抵消了部署非接触式技术所产生的成本。非接触式科技有潜力实现或改善更精简、自主和愉快的消费者体验，其核心是便利性。

此外，透过语音辨识软体，使用者可以口头执行任务。例子包括苹果的 Siri、谷歌的 Home 和亚马逊的 Alexa。小型企业已经创建了用于商业和公共用途的语音辨识软体，例如声控 ATM 和火车票务设备。企业可以减少打字时间，取消保留手动记录，并使客户能够透过使用语音启动的非接触式设备以声音方式将事件添加到他们的日历中。

此外，非接触式手势识别可以根据已知的商店扒手和吵闹顾客的资料库对进入商店的每个人进行筛选，从而识别并防止重复犯罪。当配备人脸辨识软体的摄影机识别出违法者时，该系统会快速向工作人员提供违法者的身份、店内位置以及屏蔽原因，以确保适当且安全地接近该人。透过建立已知违规者的黑名单，可以减少和消除错误和偏见。此外，该策略还解放了防损人员，使他们能够专注于确保客户和员工的安全。

基于非接触式手势识别的销售点 (POS) 系统可以快速、轻鬆地验证客户身份并允许付款。与先前的生物辨识技术类似，客户不需要信用卡或智慧型手机即可完成交易。使用手势识别技术可以帮助阻止诈骗交易。即使用户的卡片或智慧型手机被盗，最新的反欺骗技术也能阻止窃贼欺骗脸部辨识系统。该技术透过确保镜头前的脸部是真人并且与资料库匹配来防止欺骗行为。

根据美国人口普查局的数据，到2022年底，零售总额将达到约7.1兆美元，比前一年增加约5亿美元。沃尔玛、好市多、亚马逊等几家世界顶尖零售公司的总部都位于美国。尤其是亚马逊，随着电子商务的全球扩张，收入出现了惊人的成长。如此巨大的零售额预计将推动所研究的市场。

亚太地区成长最快

根据统计和计画实施部 (MOSPI) 的数据，印度消费者支出从 2022 年第二季的 220798.1 亿印度卢比（2,463.2 亿美元）攀升至第三季的 222957.2 亿印度卢比（2,530.7 亿美元）。此外，根据日本统计局的数据，2021年家庭平均每月在线上购买食品的支出超过2,300日元，而家用电子产品的支出仅超过1,200日元。 2021年，家庭每月线上支出接近16,000日圆。这可能为零售企业创造机会部署手势识别系统以增强客户体验。

此外，根据全球农业资讯网预测，到2022年，印度将有约1,300万家零售杂货店。在该类别中，这包括传统零售商和新零售商。儘管自 2013 年以来数量持续增长，但主要由传统商店组成。此外，根据中国国家统计局的数据，2021年，全国零售连锁店数量为292,383家。

未来的研究应该扩展所提出的技术并将其与物联网（IoT）集成，以实现完全自动化并提高在不太理想的条件下的手势识别分割性能。为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、眼镜或眼睑遮挡、照明、非合作样本和镜面反射等，提出一种基于深度学习的高效虹膜影像分割技术发展了。

市场上的供应商正在开发新产品以占领市场份额。例如，2022年3月，人工智慧云端供应商百度人工智慧云端推出了人工智慧手语平台，能够在几分钟内产生用于手语翻译和现场口译的数位化身。该平台作为百度人工智慧云端数位化身平台西灵的新产品发布，承诺透过增加自动手语翻译的机会来帮助聋哑和听力障碍（DHH）社群打破沟通障碍。

随着中国经济的发展，消费者的需求以及生活和消费模式发生了显着变化。零售品牌和购物中心持续积极抓住新消费创造的商机，不仅采用新技术实现零售各环节数位化，提升全价值链效率、降低营运成本，积极创新和製定新商业模式，打造精细化零售服务、零售产品、零售空间。

零售业手势辨识概述

零售市场的手势辨识是碎片化的。一些主要参与者包括索尼公司、苹果公司和谷歌公司。产品发布、高额研发费用、合作和收购等是这些公司为维持激烈竞争而采取的主要成长策略。

2023年2月，全球全像扩增实境（「AR」）技术供应商微美全像创造了3D手势追踪演算法。这是一种监视使用者手势的方法，透过收集目标手势的位置并将其运动转换为视讯画面中的连续点轨迹，以使用数学演算法解码人类手势。三维手势追踪演算法是电脑视觉研究的一个重要领域。该系统使用手势、摄影机姿态和位置资讯来追踪使用者动作，这在一定程度上有助于解决视讯串流中的手势追踪问题。

2022 年 7 月，为各种电子应用领域的客户提供服务的全球半导体先驱意法半导体发布了最新的 FlightSense 飞行时间 (ToF) 多区域感测器。当与一套基本软体演算法一起交付时，该组合可为用户检测、手势识别和入侵者警告提供交钥匙解决方案，特别适合 PC 市场。

额外的好处：

  • Excel 格式的市场估算 (ME) 表
  • 3 个月的分析师支持

目录

第 1 章：简介

  • 研究成果
  • 研究假设
  • 研究范围

第 2 章：研究方法

第 3 章：执行摘要

第 4 章：市场动态

  • 市场概况
  • 市场驱动因素与限制简介
  • 市场驱动因素
    • 与机器交流越来越依赖手势
    • 零售业越来越多地使用支援手势识别的设备
  • 市场限制
    • 与手势辨识技术相关的演算法、数学和其他复杂性
  • 产业价值链分析
  • 产业吸引力－波特五力分析
    • 新进入者的威胁
    • 买家/消费者的议价能力
    • 供应商的议价能力
    • 替代产品的威胁
    • 竞争激烈程度

第 5 章：技术概览

第 6 章：市场细分

  • 依技术
    • 基于触摸的手势识别
    • 非接触式手势识别
  • 地理
    • 北美洲
    • 欧洲
    • 亚太
    • 拉丁美洲
    • 中东和非洲

第 7 章：竞争格局

  • 公司简介
    • 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：投资分析

第 9 章：市场机会与未来趋势

简介目录
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