The ignorance on spatial information and semantics of visual words becomes main obstacles in the bag-of-visual-words (BoW) method for image classification. To address the obstacles...
Currently, the bag of visual words (BOW) representation has received wide applications in object categorization. However, the BOW representation ignores the dependency relationshi...
Bag-of-visual Words (BoW) image representation is getting popular in computer vision and multimedia communities. However, experiments show that the traditional BoW representation ...
Abstract. Having effective and efficient methods to get access to desired images is essential nowadays with the huge amount of digital images. This paper presents an analogy betwee...
Ismail Elsayad, Jean Martinet, Thierry Urruty, Cha...
TOP-SURF is an image descriptor that combines interest points with visual words, resulting in a high performance yet compact descriptor that is designed with a wide range of conte...
In this paper, we consider the incoherence problem of the visual words in bag-of-words vocabularies. Different from existing work, which performs assignment of words based solely ...
Abstract. This paper explores techniques in the pipeline of image description based on visual codebooks suitable for video on-line processing. The pipeline components are (i) extra...
Automatic document classification is an important step in organizing and mining documents. Information in documents is often conveyed using both text and images that complement ea...
In recent years, the language model Latent Dirichlet Allocation (LDA), which clusters co-occurring words into topics, has been widely applied in the computer vision field. Howeve...
This paper reports our multimedia information retrieval experiments carried out for the ImageCLEF track (ImageCLEFwiki). The task is to answer to user information needs, i.e. quer...