- PAMI2024
- mmWave
- conference
- mmWave
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Medical Imaging
Since its inception, medical imaging has come a long way with the advancement of technology. 3D surface modeling is one such advancement that allows for the creation of detailed models of internal organs and tissues using images, infrared, and lasers. Image-based 3D models are non-invasive, quick, and cost-effective, but accuracy may be limited by image quality. Infrared 3D surface modeling uses infrared cameras to capture thermal radiation emitted by objects, providing insights into disease or injury. Laser-based 3D surface modeling creates detailed cross-sectional images of structures like blood vessels and nerves, providing high-resolution images with minimal invasiveness. Together, these techniques offer a powerful tool for diagnosis and treatment planning in medicine.
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Marr-Poggio Stereo Matching
The Marr-Poggio stereo matching method is a widely used technique for depth mapping in computer vision applications. It involves creating a depth map from a single camera image by estimating the correspondences between pixels in the two images based on the epipolar geometry model. The method has several advantages, including computational efficiency and robustness to image noise and lighting variations. However, it also has limitations, such as assuming no motion between cameras and not handling perspective distortion well. The Marr-Poggio method has numerous applications in computer vision, including object recognition and tracking.
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Light Intensity Estimation
This article explores various techniques for estimating light intensity using image, infrared, and laser technologies. Image-based methods rely on analyzing pixel values to estimate relative light intensity changes. Infrared sensors capture images of objects in dark or low-light conditions, with algorithms like Dark Object Removal identifying illuminated regions for high-resolution 3D reconstruction. Laser technology offers precise measurements of light intensity and color temperature, with Time-of-Flight methods calculating distance and reflectivity/transmissivity for 3D surface modeling. By combining these techniques, accurate 3D models can be created capturing the true essence of our physical world.
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Kinect and Structured Light Technology
In recent years, 3D surface modeling has seen a significant transformation thanks to the advancements in image recognition, infrared sensing, laser scanning, and Microsoft Kinect and Structured Light (SL) technology. The Kinect's motion tracking capabilities and SL's high-resolution imaging make it possible to create highly accurate and detailed 3D models of objects or scenes in real-time. This integration is particularly useful for applications that require both human interaction and static imagery. These technologies have numerous potential applications in various industries such as product design, virtual reality, art and architecture, medical imaging, etc.
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Key Researchers and Contributions
3D surface modeling is a crucial process in various fields such as engineering, manufacturing, architecture, and design. Image-based 3D surface modeling techniques rely on capturing images of physical surfaces and then using computer vision algorithms to extract information about the shape, texture, and features of the surface. Infrared (IR) technology offers unique advantages for 3D surface modeling due to its ability to capture invisible or diffused signals such as thermal radiation. Laser technology provides a powerful tool for 3D surface modeling by enabling precise measurement and mapping of surface features. The advancements in image, infrared, and laser-based 3D surface modeling techniques have opened up new possibilities for a wide range of applications in engineering, manufacturing, design, and beyond.