37,112 research outputs found
Sparse Radial Sampling LBP for Writer Identification
In this paper we present the use of Sparse Radial Sampling Local Binary
Patterns, a variant of Local Binary Patterns (LBP) for text-as-texture
classification. By adapting and extending the standard LBP operator to the
particularities of text we get a generic text-as-texture classification scheme
and apply it to writer identification. In experiments on CVL and ICDAR 2013
datasets, the proposed feature-set demonstrates State-Of-the-Art (SOA)
performance. Among the SOA, the proposed method is the only one that is based
on dense extraction of a single local feature descriptor. This makes it fast
and applicable at the earliest stages in a DIA pipeline without the need for
segmentation, binarization, or extraction of multiple features.Comment: Submitted to the 13th International Conference on Document Analysis
and Recognition (ICDAR 2015
SwinDocSegmenter: An End-to-End Unified Domain Adaptive Transformer for Document Instance Segmentation
Instance-level segmentation of documents consists in assigning a class-aware
and instance-aware label to each pixel of the image. It is a key step in
document parsing for their understanding. In this paper, we present a unified
transformer encoder-decoder architecture for en-to-end instance segmentation of
complex layouts in document images. The method adapts a contrastive training
with a mixed query selection for anchor initialization in the decoder. Later
on, it performs a dot product between the obtained query embeddings and the
pixel embedding map (coming from the encoder) for semantic reasoning. Extensive
experimentation on competitive benchmarks like PubLayNet, PRIMA, Historical
Japanese (HJ), and TableBank demonstrate that our model with SwinL backbone
achieves better segmentation performance than the existing state-of-the-art
approaches with the average precision of \textbf{93.72}, \textbf{54.39},
\textbf{84.65} and \textbf{98.04} respectively under one billion parameters.
The code is made publicly available at:
\href{https://github.com/ayanban011/SwinDocSegmenter}{github.com/ayanban011/SwinDocSegmenter}Comment: Accepted to ICDAR 2023 (San Jose, California
Coordinating views for data visualisation and algorithmic profiling
A number of researchers have designed visualisation systems that consist of multiple components, through which data and interaction commands flow. Such multistage (hybrid) models can be used to reduce algorithmic complexity, and to open up intermediate stages of algorithms for inspection and steering. In this paper, we present work on aiding the developer and the user of such algorithms through the application of interactive visualisation techniques. We present a set of tools designed to profile the performance of other visualisation components, and provide further functionality for the exploration of high dimensional data sets. Case studies are provided, illustrating the application of the profiling modules to a number of data sets. Through this work we are exploring ways in which techniques traditionally used to prepare for visualisation runs, and to retrospectively analyse them, can find new uses within the context of a multi-component visualisation system
Extraction of Projection Profile, Run-Histogram and Entropy Features Straight from Run-Length Compressed Text-Documents
Document Image Analysis, like any Digital Image Analysis requires
identification and extraction of proper features, which are generally extracted
from uncompressed images, though in reality images are made available in
compressed form for the reasons such as transmission and storage efficiency.
However, this implies that the compressed image should be decompressed, which
indents additional computing resources. This limitation induces the motivation
to research in extracting features directly from the compressed image. In this
research, we propose to extract essential features such as projection profile,
run-histogram and entropy for text document analysis directly from run-length
compressed text-documents. The experimentation illustrates that features are
extracted directly from the compressed image without going through the stage of
decompression, because of which the computing time is reduced. The feature
values so extracted are exactly identical to those extracted from uncompressed
images.Comment: Published by IEEE in Proceedings of ACPR-2013. arXiv admin note: text
overlap with arXiv:1403.778
Reverse-engineering of architectural buildings based on an hybrid modeling approach
We thank MENSI and REALVIZ companies for their helpful comments and the following people for providing us images from their works: Francesca De Domenico (Fig. 1), Kyung-Tae Kim (Fig. 9). The CMN (French national center of patrimony buildings) is also acknowledged for the opportunity given to demonstrate our approach on the Hotel de Sully in Paris. We thank Tudor Driscu for his help on the English translation.This article presents a set of theoretical reflections and technical demonstrations that constitute a new methodological base for the architectural surveying and representation using computer graphics techniques. The problem we treated relates to three distinct concerns: the surveying of architectural objects, the construction and the semantic enrichment of their geometrical models, and their handling for the extraction of dimensional information. A hybrid approach to 3D reconstruction is described. This new approach combines range-based modeling and image-based modeling techniques; it integrates the concept of architectural feature-based modeling. To develop this concept set up a first process of extraction and formalization of architectural knowledge based on the analysis of architectural treaties is carried on. Then, the identified features are used to produce a template shape library. Finally the problem of the overall model structure and organization is addressed
PROJECT ÉVORA 3D: RESEARCH, METHODOLOGY, RECONSTRUCTION AND VISUALIZATION
The Évora 3D project was born from the collaboration between the Municipality
and the University of Évora, through the two research centres of CIDEHUS1 and
CHAIA2, with the objective of completing a virtual reconstruction of the city in a longtime frame. In the national and international context, the use of new technologies has led to the diversification of this type of proposal, both at the urban level and in the
reconstruction of concrete spaces. The application of this same model to Évora, contemplating several chronological layers, seems to impose itself in a city that, in the medieval and modern periods, was one of the most important of the kingdom, as Court city, and that today is classified as World Heritage Site
Design and quality standards for custom hybrid microcircuits
A hybrid microcircuit standard was developed after a thorough review of applicable NASA, military, industry, and technical society specifications and standards and compilation of comments from technical reviewers throughout the hybrid industry. The draft of the standard submitted to the technical reviewers, the comments from the reviewers, and the completed standard are discussed
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