We propose an approach for recognizing the pose and surface material of diverse objects,leveraging diffuse reflection principles and data *** theoretical analysis and the derivation of factors influencing diffuse refl...
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We propose an approach for recognizing the pose and surface material of diverse objects,leveraging diffuse reflection principles and data *** theoretical analysis and the derivation of factors influencing diffusereflection on objects,the method concentrates on and exploits surface *** validate the feasibility of our theoretical research,the depth and active infrared intensity data obtained from a single time-of-flight camera are initially ***,these data undergo processing using feature extraction and lightweight machine-learning *** addition,an optimization method is introduced to enhance the fitting of *** experimental results not only visually showcase the effectiveness of our proposed method in accurately detecting the positions and surface materials of targets with varying sizes and spatial locations but also reveal that the vast majority of the sample data can achieve a recognition accuracy of 94.8%or higher.
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