Search results for " indexing"
showing 10 items of 88 documents
A New Class of Searchable and Provably Highly Compressible String Transformations
2019
The Burrows-Wheeler Transform is a string transformation that plays a fundamental role for the design of self-indexing compressed data structures. Over the years, researchers have successfully extended this transformation outside the domains of strings. However, efforts to find non-trivial alternatives of the original, now 25 years old, Burrows-Wheeler string transformation have met limited success. In this paper we bring new lymph to this area by introducing a whole new family of transformations that have all the "myriad virtues" of the BWT: they can be computed and inverted in linear time, they produce provably highly compressible strings, and they support linear time pattern search direc…
Unifying Textual and Visual Cues for Content-Based Image Retrieval on the World Wide Web
1999
A system is proposed that combines textual and visual statistics in a single index vector for content-based search of a WWW image database. Textual statistics are captured in vector form using latent semantic indexing based on text in the containing HTML document. Visual statistics are captured in vector form using color and orientation histograms. By using an integrated approach, it becomes possible to take advantage of possible statistical couplings between the content of the document (latent semantic content) and the contents of images (visual statistics). The combined approach allows improved performance in conducting content-based search. Search performance experiments are reported for…
Video Indexing Using MPEG Motion Compensation Vectors
2003
In the last years a lot of work has been done on color, textural, structural and semantic indexing of "content-based" video databases. Motion-based video indexing has been less explored, with approaches generally based on the analysis of optical flows. Compressed videos require the decompression of the sequences and the computation of optical flows, two steps computationally heavy. In this paper we propose some methods to index videos by motion features (mainly related to camera motion) and by motion-based spatial segmentation of frames, in a fully automatic way. Our idea is to use MPEG motion vectors as an alternative to optical flows. Their extraction is very simple and fast; it doesn't r…
Video indexing using optical flow field
2002
The increasing development of advanced multimedia applications requires new technologies for organizing and retrieving by content databases of digital video. Several content based features (color, texture, motion, etc.) are needed to perform a reliable content based retrieval. We present a method for automatic motion based video indexing and retrieval. A prototypal system has been developed to prove the validity of our approach. Our system automatically splits a video into a sequence of shots, extracts a few representative frames (said r-frames) from each shot and computes some motion based features related to the optical flow field. Motion based queries are then performed either in a quali…
A Study on Classification Methods Applied to Sentiment Analysis
2013
Sentiment analysis is a new area of research in data mining that concerns the detection of opinions and/or sentiments in texts. This work focuses on the application and the comparison of three classification techniques over a text corpus composed of reviews of commercial products in order to detect opinions about them. The chosen domain is about "perfumes", and user opinions composing the corpus are written in Italian language. The proposed approach is completely data-driven: a Term Frequency / Inverse Document Frequency (TFIDF) terms selection procedure has been applied in order to make computation more efficient, to improve the classification results and to manage some issues related to t…
Motion and Color Based Video Indexing and Retrieval
1996
In this paper we present a method for automatic motion and color based video indexing and retrieval. Our system automatically splits a video into a sequence of shots and extracts a few representative frames (r-frames) from each shot. For each r-frame we compute the optical flow field; motion features are then derived from the flow field. Color features are related to the three-dimensional RGB color histogram. Queries (direct or by example) are based on these features. Obtained results proved that motion and color based querying can play a central role in content based video retrieval
JACOB: Just A COntent Based query system for video databases
1996
The increasing development of advanced multimedia applications requires new technologies for organizing and retrieving by content databases of still digital images or digital video sequences. The authors describe JACOB, a prototypal system allowing content-based browsing and querying in video databases. The JACOB system automatically splits a video into a sequence of shots, extracts a few representative frames (said r-frames) from each shot and computes r-frame descriptors based on features like color and texture. No user action is required during the database population step. Queries exploit this image content description and may be direct or by example
Combining textual and visual cues for content-based image retrieval on the World Wide Web
2002
A system is proposed that combines textual and visual statistics in a single index vector for content-based search of a WWW image database. Textual statistics are captured in vector form using latent semantic indexing (LSI) based on text in the containing HTML document. Visual statistics are captured in vector form using color and orientation histograms. By using an integrated approach, it becomes possible to take advantage of possible statistical couplings between the content of the document (latent semantic content) and the contents of images (visual statistics). The combined approach allows improved performance in conducting content-based search. Search performance experiments are report…
Optimisation des requêtes de similarité dans les espaces métriques répondant aux besoins des usagers
2012
The complexity of data stored in large databases has increased at very fast paces. Hence, operations more elaborated than traditional queries are essential in order to extract all required information from the database. Therefore, the interest of the database community in similarity search has increased significantly. Two of the well-known types of similarity search are the Range (Rq) and the k-Nearest Neighbor (kNNq) queries, which, as any of the traditional ones, can be sped up by indexing structures of the Database Management System (DBMS). Another way of speeding up queries is to perform query optimization. In this process, metrics about data are collected and employed to adjust the par…
3D objects descriptors methods: Overview and trends
2017
International audience; Object recognition or object's category recognition under varying conditions is one of the most astonishing capabilities of human visual system. The scientists in computer vision have been trying for decades to reproduce this ability by implementing algorithms and providing computers with appropriate tools. Hence, several intelligent systems have been proposed. To act in this field, numerous approaches have been proposed. In this paper we present an overview of the current trend in 3D objects recognition and describe some representative state of the art methods, highlighting their limits and complexity.