Bag-of-feature technique is a popular approach in areas of computer vision and pattern recognition. Recently, it plays an important role in shape analysis community and especially in 3D-model retrieval. We present our approach for partial 3D-model retrieval using this technique based on closed curves. We define an invariant scalar function on the surface based on the commute-time distance. Our ...

Repetition is very common. Adaptive language models, which allow probabilities to change or adapt after seeing just a few words of a text, were introduced in speech recognition to account for text cohesion. Suppose a document mentions Noriega once. What is the chance that he will be mentioned again? if the first instance has probability p, then under standard (bag-of words) independence assumpt...

In order to perform the document-query similarity, many information retrieval (IR) models represent documents and queries as sets of weighted key words, called « bag of words », or a bag of concepts derived from a linguistic ontology, or constructed automatically by LSI or LDA techniques, to fill the gap between the query vocabulary and the one used in the document. Recent approaches propose to...

This paper proposes new hash functions for indexing local image descriptors. These functions are first applied and evaluated as a range neighbor algorithm. We show that it obtains similar results as several state of the art algorithms. In the context of near duplicate image retrieval, we integrated the proposed hash functions within a bag of words approach. Because most of the other methods use...

Recently, extensive research efforts have been dedicated to view-based 3D object retrieval, owing its advantage of using a set 2D images represent objects. Some existing image processing technologies can be employed. In this paper, we adopt Bag-of-Words for retrieval. Instead SIFT, DSP-SIFT is extracted from all as features. Moreover, two codebooks the same size are generated by approximate k-m...

Researchers have recently focused their attention on Content-Based Image Retrieval (CBIR). It has emerged as one of the most fascinating areas in image processing and computer vision. With CBIR, comparable pictures that match query are pulled from an database. As a result, it necessitates feature extraction (Local / Global) similarity calculation. This paper uses CBIR technique to determine ima...

Community question answering (cQA), which provides a platform for people with diverse background to share information and knowledge, has become an increasingly popular research topic. In this paper, we focus on the task of question retrieval. The key problem of question retrieval is to measure the similarity between the queried questions and the historical questions which have been solved by ot...

The recognition of landmarks in images can help to manage large image collections and thus is desirable for many image retrieval applications. A practical system has to be scalable with an increasing number of landmarks. For the domain of landmark recognition we investigate state-of-the-art CBIR methods on an image dataset of 900 landmarks. Our experiments show that the kNN classifier outperfor...

Nowadays, multimedia documents composed of text and images are increasingly used, thanks to the Internet and the increasing capacity of data storage. It is more and more important to be able to retrieve needles in this huge haystack. In this paper, we present a multimedia document model which combines textual and visual information. Using a bag-of-words approach, it represents a textual and vis...

In this paper, we describe our approach to the French English Bilingual Task in CLEF 2001. A simple dictionary-based method is used to translate the French query into a bag of weighted English words, the English query, which is submitted to the SMART retrieval engine. Despite the simplicity of the method, the results happen to be reasonable.