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Early gesture recognition was based on the recognition technology of two-dimensional color images. The so-called two-dimensional color image refers to the two-dimensional static image obtained after the scene is photographed by an ordinary camera, and then the content in the image is recognized by computer graphics algorithms. Two-dimensional hand shape recognition can only recognize a few static gestures, and these gestures must be preset in advance. Compared with two-dimensional gesture recognition, three-dimensional gesture recognition adds a Z-axis information, which can recognize various hand shapes, gestures and actions. Three-dimensional gesture recognition is also the main direction of gesture recognition development. However, this kind of gesture recognition containing certain depth information requires special hardware to implement. Common ones are completed by sensors and optical cameras. The most critical part of gesture recognition includes tracking gestures and subsequent computer data processing. Gesture capture is mainly achieved through optics and sensors. The algorithms for gesture recognition inference include template matching technology (used by two-dimensional gesture recognition technology), statistical sample features, and deep learning neural network technology. According to the type of camera (2D camera, depth camera), it can be divided into two categories: 1) two-dimensional gesture recognition based on 2D camera and 2) three-dimensional gesture recognition based on 3D camera (such as Microsoft's kinnect). This article focuses on gesture recognition using a 2D camera.

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Early gesture recognition was based on the recognition technology of two-dimensional color images. The so-called two-dimensional color image refers to the two-dimensional static image obtained after the scene is photographed by an ordinary camera, and then the content in the image is recognized by computer graphics algorithms. Two-dimensional hand shape recognition can only recognize a few static gestures, and these gestures must be preset in advance. Compared with two-dimensional gesture recognition, three-dimensional gesture recognition adds a Z-axis information, which can recognize various hand shapes, gestures and actions. Three-dimensional gesture recognition is also the main direction of gesture recognition development. However, this kind of gesture recognition containing certain depth information requires special hardware to implement. Common ones are completed by sensors and optical cameras. The most critical part of gesture recognition includes tracking gestures and subsequent computer data processing. Gesture capture is mainly achieved through optics and sensors. The algorithms for gesture recognition inference include template matching technology (used by two-dimensional gesture recognition technology), statistical sample features, and deep learning neural network technology. According to the type of camera (2D camera, depth camera), it can be divided into two categories: 1) two-dimensional gesture recognition based on 2D camera and 2) three-dimensional gesture recognition based on 3D camera (such as Microsoft's kinnect). This article focuses on gesture recognition using a 2D camera.

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The global 2D Gesture Recognition Systems market size is expected to reach $ 159.1 million by 2030, rising at a market growth of 5.7% CAGR during the forecast period (2024-2030).

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According to our (Global Info Research) latest study, the global 2D Gesture Recognition Systems market size was valued at USD 107.6 million in 2023 and is forecast to a readjusted size of USD 159.1 million by 2030 with a CAGR of 5.7% during review period.

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The global 2D Gesture Recognition for Consumer Electronics market size is expected to reach $ 89 million by 2030, rising at a market growth of 5.2% CAGR during the forecast period (2024-2030).

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According to our (Global Info Research) latest study, the global 2D Gesture Recognition for Consumer Electronics market size was valued at USD 62 million in 2023 and is forecast to a readjusted size of USD 89 million by 2030 with a CAGR of 5.2% during review period.

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According to the type of camera (2D camera, depth camera), it can be divided into two categories: 1) 2D gesture recognition based on 2D camera and 2) 3D gesture recognition based on 3D camera (such as Microsoft Kinnect). Early gesture recognition is based on two-dimensional color image recognition technology. The so-called two-dimensional color image refers to the two-dimensional static image obtained after the scene is shot by the ordinary camera, and then the content in the image is recognized by the computer graphics algorithm. Two-dimensional hand recognition can only identify a few static gestures, and these gestures must be preset in advance. Compared with 2D gesture recognition, 3D gesture recognition adds a Z-axis information, which can recognize various hand shapes, gestures and movements. Three-dimensional gesture recognition is also the main direction of gesture recognition development. However, this kind of gesture recognition, which contains some depth information, needs special hardware to realize. The common ones are sensors and optical cameras. The most important part of gesture recognition includes the tracking of gesture and the subsequent computer data processing. Gesture capture is mainly achieved through optical and sensor two ways. Gesture recognition prediction algorithms, including template matching technology (used in two-dimensional gesture recognition technology), through statistical sample features and deep learning neural network technology.

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According to our (Global Info Research) latest study, the global 2D Gesture Recognition Systems market size was valued at USD 107.6 million in 2022 and is forecast to a readjusted size of USD 159.1 million by 2029 with a CAGR of 5.7% during review period. The influence of COVID-19 and the Russia-Ukraine War were considered while estimating market sizes.

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This report studies the global 2D Gesture Recognition for Consumer Electronics production, demand, key manufacturers, and key regions.

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According to our (Global Info Research) latest study, the global 2D Gesture Recognition for Consumer Electronics market size was valued at USD million in 2022 and is forecast to a readjusted size of USD million by 2029 with a CAGR of % during review period. The influence of COVID-19 and the Russia-Ukraine War were considered while estimating market sizes.

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