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shape-based retrieval and analysis 2004 [53] [54] Shilane et al. Berkeley 3-D Object Dataset (B3DO) Depth and color images collected from crowdsourced Microsoft Kinect users. Annotated in 50 object categories. 849 images, in 75 scenes color image, depth image, object class, bounding boxes, 3D center points Predict bounding boxes 2011, updated ...
In image processing, the input is an image and the output is an image as well, whereas in computer vision, an image or a video is taken as an input and the output could be an enhanced image, an understanding of the content of an image or even behavior of a computer system based on such understanding.
Image analysis or imagery analysis is the extraction of meaningful information from images; mainly from digital images by means of digital image processing techniques. [1] Image analysis tasks can be as simple as reading bar coded tags or as sophisticated as identifying a person from their face .
Image registration is the process of transforming different sets of data into one coordinate system. Data may be multiple photographs, data from different sensors, times, depths, or viewpoints. [1] It is used in computer vision, medical imaging, [2] military automatic target recognition, and compiling and analyzing images and data from ...
2D digital image acquisition is the information source of 3D reconstruction. Commonly used 3D reconstruction is based on two or more images, although it may employ only one image in some cases. There are various types of methods for image acquisition that depends on the occasions and purposes of the specific application.
Many of the techniques of digital image processing, or digital picture processing as it often was called, were developed in the 1960s, at Bell Laboratories, the Jet Propulsion Laboratory, Massachusetts Institute of Technology, University of Maryland, and a few other research facilities, with application to satellite imagery, wire-photo standards conversion, medical imaging, videophone ...
Computational imaging systems span a broad range of applications. While applications such as SAR, computed tomography, seismic inversion are well known, they have undergone significant improvements (faster, higher-resolution, lower dose exposures [3]) driven by advances in signal and image processing algorithms (including compressed sensing techniques), and faster computing platforms.
[1] [2] [3] Computer vision tasks include methods for acquiring digital images (through image sensors), image processing, and image analysis, to reach an understanding of digital images. In general, it deals with the extraction of high-dimensional data from the real world in order to produce numerical or symbolic information that the computer ...