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Last Updated: Apr 25, 2025 | Study Period: 2024-2030
A visual artificial intelligence technique called object recognition may recognise things in a still or moving image. The development of deep learning and machine learning algorithms led to the development of this technology.
When people using this technology examine a photo or watch a video, they may swiftly recognise persons, objects, and many other elements in the image.
The aim of work on object identification technology is frequently to enable artificial intelligence to learn things about human nature and objects that people use.
Object recognition is the process of confidently recognising, locating, and classifying items in images from a photo or video.
The Global Object Recognition Camera market accounted for $XX Billion in 2022 and is anticipated to reach $XX Billion by 2030, registering a CAGR of XX% from 2024 to 2030.
By employing object recognition rather than motion detection, false alarms are eliminated while simultaneously offering insightful data about operations and business.
The most recent lineup of five cameras captures high-quality photos at up to 2MP resolution and includes potent, in-camera deep learning algorithms for sophisticated object detection, classification, and error-free analytics.
The new cameras can identify and categorise objects like faces, licence plates, and people as well as cars and people. It has a feature called "BestShot" that chooses the most appropriate image of a categorised object to be delivered to a backend server.
Along with the video information, the objects' distinct characteristics, such as clothing colours, age groups, vehicle types, and colours, are also stored as metadata.
The overall search efficiency is increased as a result of avoiding server overload and enabling quick AI-driven search for information extraction on specific items.
Additionally, they support the most recent noise reduction technology, WiseNRII (Wise Noise Reduction II), which makes use of AI object detection technology to recognise object appearance or movements and remove motion blur adaptively in low-light settings with a lot of noise.
Blurred images and other issues brought on by excessive noise reduction are successfully addressed by this.Additionally, the company's exclusive WiseStreamIII technology is supported by Wisenet P series AI 2MP cameras.
Based on edge-based artificial intelligence, it recognises important things, such as people and/or automobiles, and greatly reduces background data.
| Sl no | Topic |
| 1 | Market Segmentation |
| 2 | Scope of the report |
| 3 | Abbreviations |
| 4 | Research Methodology |
| 5 | Executive Summary |
| 6 | Introduction |
| 7 | Insights from Industry stakeholders |
| 8 | Cost breakdown of Product by sub-components and average profit margin |
| 9 | Disruptive innovation in the Industry |
| 10 | Technology trends in the Industry |
| 11 | Consumer trends in the industry |
| 12 | Recent Production Milestones |
| 13 | Component Manufacturing in US, EU and China |
| 14 | COVID-19 impact on overall market |
| 15 | COVID-19 impact on Production of components |
| 16 | COVID-19 impact on Point of sale |
| 17 | Market Segmentation, Dynamics and Forecast by Geography, 2024-2030 |
| 18 | Market Segmentation, Dynamics and Forecast by Product Type, 2024-2030 |
| 19 | Market Segmentation, Dynamics and Forecast by Application, 2024-2030 |
| 20 | Market Segmentation, Dynamics and Forecast by End use, 2024-2030 |
| 21 | Product installation rate by OEM, 2023 |
| 22 | Incline/Decline in Average B-2-B selling price in past 5 years |
| 23 | Competition from substitute products |
| 24 | Gross margin and average profitability of suppliers |
| 25 | New product development in past 12 months |
| 26 | M&A in past 12 months |
| 27 | Growth strategy of leading players |
| 28 | Market share of vendors, 2023 |
| 29 | Company Profiles |
| 30 | Unmet needs and opportunity for new suppliers |
| 31 | Conclusion |
| 32 | Appendix |
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