PicToSeek: combining color and shape invariant features for image retrieval

By Theo Gevers, Arnold M. W. Smeulders. IEEE Transactions on Image Processing, 2000

591 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Media Technology

View Paper: https://www.semanticscholar.org/paper/9da15b932df57a8f959471ebc977d620efb18cc1

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In Computer Vision and Pattern Recognition

In Media Technology

Citations in the corpus

A Region-Based Fuzzy Feature Matching Approach to Content-Based Image Retrieval (2002, methodology): “Content-based image retrieval (CBIR) is aimed at eÆcient retrieval of relevant images from large image databases based on automatically derived imagery features.”
A survey on the use of pattern recognition methods for abstraction, indexing and retrieval of images and video (2002, methodology): “PicToSeek: The PicToSeek 7 system [20] uses the color variation, saturation, transition strength, background and grayness as the indexing features to provide content based access to images.”
Color Invariants for Person Reidentification (2013, background): “Index Terms—Surveillance applications, person reidentification, color invariant signatures Ç”
CLUE: cluster-based retrieval of images by unsupervised learning (2005, methodology): “Examples include IBM QBIC System [10], MIT Photobook System [29], Berkeley Chabot [28] and Blobworld Systems [4], Virage System [14], Columbia VisualSEEK and WebSEEK Systems [42], the PicHunter System [8], UCSB NeTra System [23], UIUC MARS System [25], the PicToSeek System [13], and Stanford WBIIS [”
Content based image retrieval using motif cooccurrence matrix (2004, background): “A number of general purpose CBIR systems have been built since then [7–9], which are capable of supporting new algorithms as they are developed.”
Palette power: enabling visual search through colors (2013, methodology): “Higher level shape invariants such as angle between two color edges and the cross-ratio between four color edges are also used [8].”
Concept-Based Video Retrieval (2009, background): “Research in content-based retrieval has resulted in a wide variety of image and video search systems [17, 32, 34, 61, 67, 72, 114, 143, 180, 197, 207, 214, 258, 266].”
CSIFT: A SIFT Descriptor with Color Invariant Characteristics (2006, background): “ample, in [12], color and shape invariants are combined for image retrieval.”
Image retrieval: Ideas, influences, and trends of the new age (2008, unknown): “Pictoseek: Combining color and shape invariant features for image retrieval.”
Computer-aided tumor detection in endoscopic video using color wavelet features (2003, background): “Assuming dichromatic reflection and white illumination, a color transform that is independent of the viewpoint, surface orientation , illumination direction, and illumination intensity, has been proposed by Gevers [48].”