Search results
Results from the WOW.Com Content Network
A useful extension to the original operator is the so-called uniform pattern, [8] which can be used to reduce the length of the feature vector and implement a simple rotation invariant descriptor. This idea is motivated by the fact that some binary patterns occur more commonly in texture images than others.
The Computer Vision and Image Processing Algorithm Test and Analysis Tool, CVIP-ATAT, creates human and computer vision applications. Its primary use is to execute algorithms for processing multiple images at a time, incorporating various algorithmic and parameter variations. The program determines a suitable algorithm for pre-processing ...
Computer vision is an interdisciplinary field that deals with how computers can be made to gain high-level understanding from digital images or videos.From the perspective of engineering, it seeks to automate tasks that the human visual system can do.
"IMMI - Rapidminer Image Mining Extension". Archived from the original on 2022-07-03. - open-source tool for image mining "Robust Real-Time Face Detection" (PDF). Archived from the original (PDF) on 2019-02-02. An improved algorithm on Viola-Jones object detector; Citations of the Viola–Jones algorithm in Google Scholar
The following is a non-complete list of applications which are studied in computer vision. In this category, the term application should be interpreted as a high level function which solves a problem at a higher level of complexity. Typically, the various technical problems related to an application can be solved and implemented in different ways.
Computer Vision Annotation Tool (CVAT) is a free, open source, web-based image and video annotation tool used for labeling data for computer vision algorithms. Originally developed by Intel , CVAT is designed for use by a professional data annotation team, with a user interface optimized for computer vision annotation tasks.
The Caltech 101 data set was used to train and test several computer vision recognition and classification algorithms. The first paper to use Caltech 101 was an incremental Bayesian approach to one-shot learning, [ 4 ] an attempt to classify an object using only a few examples, by building on prior knowledge of other classes.
Images plus .mat file labels Human pose estimation 2011 [196] S. Johnson and M. Everingham MCQ Dataset 6 different real multiple choice-based exams (735 answer sheets and 33,540 answer boxes) to evaluate computer vision techniques and systems developed for multiple choice test assessment systems. None 735 answer sheets and 33,540 answer boxes