Annotation

About: Annotation is a research topic. Over the lifetime, 6719 publications have been published within this topic receiving 203463 citations. The topic is also known as: note & markup.

Annotations as multiple perspectives of video content

Abstract: This paper describes a video annotation tool based on a new and flexible model, that gives several perspectives over the same video content. The model was designed in a way that allows having multiple views over the same video data, enabling users with different requirements to have the most appropriate interface. These views, video-lenses, highlight a specific aspect of the video content that is being annotated. Annotations are made using a timeline based interface with multiple tracks, where each track corresponds to a given video-lens. The format used to store and exchange the information is the MPEG-7 standard. The annotation tool (VAnnotator) is being developed in the scope of Vizard, an ambitious project that aims to define a new paradigm for video navigation, annotation, editing and retrieval. The Vizard project includes users, both from the production/archiving area and from the consumer electronics area, that help to define and validate the annotation requirements and functionality.

Scalable search-based image annotation

Abstract: With the popularity of digital cameras, more and more people have accumulated considerable digital images on their personal devices. As a result, there are increasing needs to effectively search these personal images. Automatic image annotation may serve the goal, for the annotated keywords could facilitate the search processes. Although many image annotation methods have been proposed in recent years, their effectiveness on arbitrary personal images is constrained by their limited scalability, i.e. limited lexicon of small-scale training set. To be scalable, we propose a search-based image annotation algorithm that is analogous to information retrieval. First, content-based image retrieval technology is used to retrieve a set of visually similar images from a large-scale Web image set. Second, a text-based keyword search technique is used to obtain a ranked list of candidate annotations for each retrieved image. Third, a fusion algorithm is used to combine the ranked lists into a final candidate annotation list. Finally, the candidate annotations are re-ranked using Random Walk with Restarts and only the top ones are reserved as the final annotations. The application of both efficient search techniques and Web-scale image set guarantees the scalability of the proposed algorithm. Moreover, we provide an annotation rejection scheme to point out the images that our annotation system cannot handle well. Experimental results on U. Washington dataset show not only the effectiveness and efficiency of the proposed algorithm but also the advantage of image retrieval using annotation results over that using visual features.

PIR: a new resource for bioinformatics.

Abstract: Summary: The Protein Information Resource (PIR) has greatly expanded its Web site and developed a set of interactive search and analysis tools to facilitate the analysis, annotation, and functional identification of proteins New search engines have been implemented to combine sequence similarity search results with database annotation information The new PIR search systems have proved very useful in providing enriched functional annotation of protein sequences, determining protein superfamily-domain relationships, and detecting annotation errors in genomic database archives Availability: http:// pirgeorgetownedu/

Long-Read Annotation: Automated Eukaryotic Genome Annotation Based on Long-Read cDNA Sequencing.

Abstract: Single-molecule full-length complementary DNA (cDNA) sequencing can aid genome annotation by revealing transcript structure and alternative splice forms, yet current annotation pipelines do not incorporate such information. Here we present long-read annotation (LoReAn) software, an automated annotation pipeline utilizing short- and long-read cDNA sequencing, protein evidence, and ab initio prediction to generate accurate genome annotations. Based on annotations of two fungal genomes (Verticillium dahliae and Plicaturopsis crispa) and two plant genomes (Arabidopsis [Arabidopsis thaliana] and Oryza sativa), we show that LoReAn outperforms popular annotation pipelines by integrating single-molecule cDNA-sequencing data generated from either the Pacific Biosciences or MinION sequencing platforms, correctly predicting gene structure, and capturing genes missed by other annotation pipelines.

Method and system for propagating annotations using pattern matching

Abstract: Methods, systems, and articles of manufacture for propagating annotations created for data objects appearing in a variety of different application types are provided. Some embodiments present users collaborating on a project with an indication of data objects in a current document that have been annotated, or that related data objects have been annotated, in other documents. Users may then review the annotations and selectively associate the annotations with the related data object in the current document, thereby spreading the tacit knowledge reflected in the annotation about related data objects across many documents in an enterprise network. Further, an annotation management system may maintain a thesaurus of related terms and corresponding annotation points to find annotations for data objects that exist in other documents without having to inspect the data object(s) associated with each existing annotation.