Image (mathematics)
Related papers: 20
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In mathematics and computer vision, an **image** refers to the output of a function mapping an input domain (such as a 2D sensor array) to a range of values representing measurements like intensity, color, or depth. In robotics and AI, images serve as the primary sensory input for perceiving and interpreting the environment — captured by cameras, depth sensors, or LiDAR systems and processed to extract meaningful information about objects, scenes, and spatial relationships. Images underpin a vast range of robotic capabilities: autonomous vehicles use them for obstacle detection and lane following, manipulators rely on them for object recognition and grasp planning, and SLAM systems use image sequences to build maps and estimate pose. Techniques such as convolutional neural networks, feature descriptors, and point cloud processing all operate on image-derived data to enable tasks like 3D reconstruction, action recognition, and 6D pose estimation. Images matter because they provide rich, high-bandwidth environmental information that enables robots and AI systems to operate intelligently in complex, unstructured real-world settings — making image understanding foundational to nearly every modern perception pipeline.
Top Researchers
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Handbook of pattern recognition and image processing
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