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  2. List of datasets in computer vision and image processing

    en.wikipedia.org/wiki/List_of_datasets_in...

    Images Railway signal recognition 2023 [67] [68] Philipp Leibner, Fabian Hampel, Christian Schindler Multi-cue pedestrian Multi-cue onboard pedestrian detection dataset is a dataset for detection of pedestrians. The databaset is labeled box-wise. 1092 image pairs with 1776 boxes for pedestrians Images Object recognition and classification 2009 [69]

  3. Bag-of-words model in computer vision - Wikipedia

    en.wikipedia.org/wiki/Bag-of-words_model_in...

    Caltech Large Scale Image Search Toolbox: a Matlab/C++ toolbox implementing Inverted File search for Bag of Words model. It also contains implementations for fast approximate nearest neighbor search using randomized k-d tree , locality-sensitive hashing , and hierarchical k-means .

  4. Caltech 101 - Wikipedia

    en.wikipedia.org/wiki/Caltech_101

    It is intended to facilitate computer vision research and techniques and is most applicable to techniques involving image recognition classification and categorization. Caltech 101 contains a total of 9,146 images, split between 101 distinct object categories (faces, watches, ants, pianos, etc.) and a background

  5. Scale-invariant feature transform - Wikipedia

    en.wikipedia.org/wiki/Scale-invariant_feature...

    The detection and description of local image features can help in object recognition. The SIFT features are local and based on the appearance of the object at particular interest points, and are invariant to image scale and rotation. They are also robust to changes in illumination, noise, and minor changes in viewpoint.

  6. Chessboard detection - Wikipedia

    en.wikipedia.org/wiki/Chessboard_detection

    In feature extraction, one seeks to identify image interest points, which summarize the semantic content of an image and, hence, offer a reduced dimensionality representation of one's data. [2] Chessboards - in particular - are often used to demonstrate feature extraction algorithms because their regular geometry naturally exhibits local image ...

  7. Maximally stable extremal regions - Wikipedia

    en.wikipedia.org/wiki/Maximally_stable_extremal...

    This technique was proposed by Matas et al. [1] to find correspondences between image elements taken from two images with different viewpoints. This method of extracting a comprehensive number of corresponding image elements contributes to the wide-baseline matching, and it has led to better stereo matching and object recognition algorithms.

  8. Foreground detection - Wikipedia

    en.wikipedia.org/wiki/Foreground_detection

    Foreground detection is one of the major tasks in the field of computer vision and image processing whose aim is to detect changes in image sequences. Background subtraction is any technique which allows an image's foreground to be extracted for further processing (object recognition etc.).

  9. Image analysis - Wikipedia

    en.wikipedia.org/wiki/Image_analysis

    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 .