Introductory Techniques for 3-D Computer Vision

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Publisher ‏ : ‎ Prentice Hall (January 1, 1998)
Language ‏ : ‎ English
Hardcover ‏ : ‎ 343 pages
ISBN-10 ‏ : ‎ 0132611082
ISBN-13 ‏ : ‎ 978-0132611084
Item Weight ‏ : ‎ 1.57 pounds
Dimensions ‏ : ‎ 7.5 x 0.75 x 9.5 inches

3-D computer vision is a rapidly growing field that holds great promise for a wide range of applications, from augmented reality to robotics. If you’re new to the world of 3-D computer vision, here are some introductory techniques to help you get started:

1. 3-D reconstruction: One of the fundamental tasks in 3-D computer vision is to reconstruct the 3-D structure of a scene from 2-D images. This can be done using techniques such as stereo vision, structure from motion, and depth sensing. By accurately reconstructing the 3-D structure of a scene, you can enable a wide range of applications, from virtual reality to object recognition.

2. Camera calibration: Before you can accurately reconstruct a 3-D scene, you need to calibrate your cameras to ensure that they are accurately capturing the scene. Camera calibration involves determining the intrinsic and extrinsic parameters of your cameras, such as focal length, principal point, and lens distortion. By calibrating your cameras, you can ensure that your 3-D reconstructions are accurate and reliable.

3. Object recognition: Another important task in 3-D computer vision is object recognition, which involves identifying and categorizing objects in a scene. This can be done using techniques such as feature extraction, machine learning, and deep learning. By accurately recognizing objects in a scene, you can enable applications such as autonomous driving, robotic manipulation, and augmented reality.

4. Pose estimation: Pose estimation involves determining the position and orientation of objects in a scene. This can be done using techniques such as feature matching, point cloud registration, and pose optimization. By accurately estimating the pose of objects in a scene, you can enable applications such as robotic navigation, object tracking, and virtual reality.

These are just a few introductory techniques for 3-D computer vision. As you delve deeper into the field, you’ll discover a wide range of techniques and algorithms that can help you tackle complex 3-D vision tasks. With the rapid advancement of technology and the increasing availability of 3-D sensors, the possibilities for 3-D computer vision are endless.
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