Learn More
Following the success of hashing methods for multidimensional indexing, more and more works are interested in embedding visual feature space in compact hash codes. Such approaches are not an alternative to using index structures but a complementary way to reduce both the memory usage and the distance computation cost. Several data dependent hash functions(More)
This paper presents a new content-based retrieval framework applied to logo retrieval in large natural image collections. The first contribution is a new challenging dataset, called BelgaLogos, which was created in collaboration with professionals of a press agency, in order to evaluate logo retrieval technologies in real-world scenarios. The second and(More)
Content-based copy retrieval (CBCR) aims at retrieving in a database all the modified versions or the previous versions of a given candidate object. In this paper, we present a copy retrieval scheme based on local features that can deal with very large databases both in terms of quality and speed. We first propose a new approximate similarity search(More)
Efficient high-dimensional similarity search structures are essential for building scalable content-based search systems on feature-rich multimedia data. In the last decade, Locality Sensitive Hashing (LSH) has been proposed as indexing technique for approximate similarity search. Among the most recent variations of LSH, multi-probe LSH techniques have been(More)
ImageCLEF’s plant identification task provides a testbed for the system-oriented evaluation of tree species identification based on leaf images. The aim is to investigate image retrieval approaches in the context of crowdsourced images of leaves collected in a collaborative manner. This paper presents an overview of the resources and assessments of the(More)
Building accurate knowledge of the identity, the geographic distribution and the evolution of living species is essential for a sustainable development of humanity as well as for biodiversity conservation. In this context, using multimedia identification tools is considered as one of the most promising solutions to help bridging the taxonomic gap. With the(More)
Using multimedia identification tools is considered as one of the most promising solutions to help bridging the taxonomic gap and build accurate knowledge of the identity, the geographic distribution and the evolution of living species. Large and structured communities of nature observers (e.g. eBird, Xeno-canto, Tela Botanica, etc.) as well as big(More)