The approach of using Binocular stereo vision to acquire object's 3D geometric information is on the basis of visual disparity. Unfortunately, it is computationally intensive, besides it performs rather poorly when baseline distance is large. Binocular stereo vision method is well developed and stably contributes to favorable 3D reconstruction, leading to a better performance when compared to other 3D construction. In terms of trigonometry relations, depth information can be calculated from disparity. This is more direct than Monocular methods such as shape-from-shading.īinocular stereo vision method requires two identical cameras with parallel optical axis to observe one same object, acquiring two images from different points of view. Images of an object acquired by two cameras simultaneously in different viewing angles, or by one single camera at different time in different viewing angles, are used to restore its 3D geometric information and reconstruct its 3D profile and location. The results are presented in form of depth maps. Stereo vision obtains the 3-dimensional geometric information of an object from multiple images based on the research of human visual system. It has been suggested that this section be split out into another article titled Computer stereo vision. Technically, it avoids stereo correspondence, which is fairly complex. 3D reconstruction through monocular cues is simple and quick, and only one appropriate digital image is needed thus only one camera is adequate. Silhouettes, shading and texture) to measure 3D shape, and that's why it is also named Shape-From-X, where X can be silhouettes, shading, texture etc. Monocular cues methods refer to using one or more images from one viewpoint (camera) to proceed to 3D construction. By comparison to active methods, passive methods can be applied to a wider range of situations. In this case we talk about image-based reconstruction and the output is a 3D model. Typically, the sensor is an image sensor in a camera sensitive to visible light and the input to the method is a set of digital images (one, two or more) or video. Passive methods of 3D reconstruction do not interfere with the reconstructed object they only use a sensor to measure the radiance reflected or emitted by the object's surface to infer its 3D structure through image understanding.
Examples range from moving light sources, colored visible light, time-of-flight lasers to microwaves or 3D ultrasound. More applicable radiometric methods emit radiance towards the object and then measure its reflected part. A simple example of a mechanical method would use a depth gauge to measure a distance to a rotating object put on a turntable. structured light, laser range finder and other active sensing techniques. These methods actively interfere with the reconstructed object, either mechanically or radiometrically using rangefinders, in order to acquire the depth map, e.g. range data methods, given the depth map, reconstruct the 3D profile by numerical approximation approach and build the object in scenario based on model. Active methods ģD echo sounding map of an underwater canyonĪctive methods, i.e. Digital elevation models can be reconstructed using methods such as airborne laser altimetry or synthetic aperture radar. For instance, the lesion information of the patients can be presented in 3D on the computer, which offers a new and accurate approach in diagnosis and thus has vital clinical value. The 3D reconstruction of objects is a generally scientific problem and core technology of a wide variety of fields, such as Computer Aided Geometric Design ( CAGD), computer graphics, computer animation, computer vision, medical imaging, computational science, virtual reality, digital media, etc. By Using 3D reconstruction one can determine any object's 3D profile, as well as knowing the 3D coordinate of any point on the profile. The research of 3D reconstruction has always been a difficult goal.