Visual-GPS: Ego-Downward and Ambient Video Based Person Location Association

Author(s):  
Liang Yang ◽  
Hao Jiang ◽  
Zhouyuan Huo ◽  
Jizhong Xiao
Author(s):  
Jeff Blackadar

Bibliothèque et Archives Nationales du Québec digitally scanned and converted to text a large collection of newspapers to create a resource of tremendous potential value to historians. Unfortunately, the text files are difficult to search reliably due to many errors caused by the optical character recognition (OCR) text conversion process. This digital history project applied natural language processing in an R language computer program to create a new and useful index of this corpus of digitized content despite OCR related errors. The project used editions of The Equity, published in Shawville, Quebec since 1883. The program extracted the names of all the person, location and organization entities that appeared in each edition. Each of the entities was cataloged in a database and related to the edition of the newspaper it appeared in. The database was published to a public website to allow other researchers to use it. The resulting index or finding aid allows researchers to access The Equity in a different way than just full text searching. People, locations and organizations appearing in the Equity are listed on the website and each entity links to a page that lists all of the issues that entity appeared in as well as the other entities that may be related to it. Rendering the text files of each scanned newspaper into entities and indexing them in a database allows the content of the newspaper to be interacted with by entity name and type rather than just a set of large text files. Website: http://www.jeffblackadar.ca/graham_fellowship/corpus_entities_equity/


2018 ◽  
pp. 735-753
Author(s):  
Eugene Borovikov ◽  
Szilard Vajda ◽  
Michael Gill

Despite the many advances in face recognition technology, practical face detection and matching for unconstrained images remain challenging. A real-world Face Image Retrieval (FIR) system is described in this paper. It is based on optimally weighted image descriptor ensemble utilized in single-image-per-person (SIPP) approach that works with large unconstrained digital photo collections. The described visual search can be deployed in many applications, e.g. person location in post-disaster scenarios, helping families reunite quicker. It provides efficient means for face detection, matching and annotation, working with images of variable quality, requiring no time-consuming training, yet showing commercial performance levels.


2019 ◽  
Vol 30 (3) ◽  
pp. 1260-1271 ◽  
Author(s):  
He Chen ◽  
Yuji Naya

Abstract While the hippocampus (HPC) is a prime candidate combining object identity and location due to its strong connections to the ventral and dorsal pathways via surrounding medial temporal lobe (MTL) areas, recent physiological studies have reported spatial information in the ventral pathway and its downstream target in MTL. However, it remains unknown whether the object–location association proceeds along the ventral MTL pathway before HPC. To address this question, we recorded neuronal activity from MTL and area anterior inferotemporal cortex (TE) of two macaques gazing at an object to retain its identity and location in each trial. The results showed significant effects of object–location association at a single-unit level in TE, perirhinal cortex (PRC), and HPC, but not in the parahippocampal cortex. Notably, a clear area difference emerged in the association form: 1) representations of object identity were added to those of subjects’ viewing location in TE; 2) PRC signaled both the additive form and the conjunction of the two inputs; and 3) HPC signaled only the conjunction signal. These results suggest that the object and location signals are combined stepwise at TE and PRC each time primates view an object, and PRC may provide HPC with the conjunctional signal, which might be used for encoding episodic memory.


2020 ◽  
Vol 16 (3) ◽  
pp. 110-127
Author(s):  
Raabia Mumtaz ◽  
Muhammad Abdul Qadir

This article describes CustNER: a system for named-entity recognition (NER) of person, location, and organization. Realizing the incorrect annotations of existing NER, four categories of false negatives have been identified. The NEs not annotated contain nationalities, have corresponding resource in DBpedia, are acronyms of other NEs. A rule-based system, CustNER, has been proposed that utilizes existing NERs and DBpedia knowledge base. CustNER has been trained on the open knowledge extraction (OKE) challenge 2017 dataset and evaluated on OKE and CoNLL03 (Conference on Natural Language Learning) datasets. The OKE dataset has also been annotated with the three types. Evaluation results show that CustNER outperforms existing NERs with F score 12.4% better than Stanford NER and 3.1% better than Illinois NER. On another standard evaluation dataset for which the system is not trained, the CoNLL03 dataset, CustNER gives results comparable to existing systems with F score 3.9% better than Stanford NER, though Illinois NER F score is 1.3% better than CustNER.


Information ◽  
2018 ◽  
Vol 9 (12) ◽  
pp. 297 ◽  
Author(s):  
Yalemisew Abgaz ◽  
Amelie Dorn ◽  
Barbara Piringer ◽  
Eveline Wandl-Vogt ◽  
Andy Way

Extensive collections of data of linguistic, historical and socio-cultural importance are stored in libraries, museums and national archives with enormous potential to support research. However, a sizable portion of the data remains underutilised because of a lack of the required knowledge to model the data semantically and convert it into a format suitable for the semantic web. Although many institutions have produced digital versions of their collection, semantic enrichment, interlinking and exploration are still missing from digitised versions. In this paper, we present a model that provides structure and semantics to a non-standard linguistic and historical data collection on the example of the Bavarian dialects in Austria at the Austrian Academy of Sciences. We followed a semantic modelling approach that utilises the knowledge of domain experts and the corresponding schema produced during the data collection process. The model is used to enrich, interlink and publish the collection semantically. The dataset includes questionnaires and answers as well as supplementary information about the circumstances of the data collection (person, location, time, etc.). The semantic uplift is demonstrated by converting a subset of the collection to a Linked Open Data (LOD) format, where domain experts evaluated the model and the resulting dataset for its support of user queries.


2014 ◽  
Vol 12 (2) ◽  
pp. 86-97
Author(s):  
Evandro B. Fonseca ◽  
Renata Vieira ◽  
Aline A. Valin

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Armir Bujari ◽  
Claudio Enrico Palazzi

The Internet edge has evolved from a simple consumer of information and data to eager producer feeding sensed data at a societal scale. The crowdsensing paradigm is a representative example which has the potential to revolutionize the way we acquire and consume data. Indeed, especially in the era of smartphones, the geographical and temporalscopusof data is often local. For instance, users’ queries are more and more frequently about a nearby object, event, person, location, and so forth. These queries could certainly be processed and answered locally, without the need for contacting a remote server through the Internet. In this scenario, the data is alimented (sensed) by the users and, as a consequence, data lifetime is limited by human organizational factors (e.g., mobility). From this basis, data survivability in the Area of Interest (AoI) is crucial and, if not guaranteed, could undermine system deployment. Addressing this scenario, we discuss and contribute with a novel protocol named AirCache, whose aim is to guarantee data availability in the AoI while at the same time reducing the data access costs at the network edges. We assess our proposal through a simulation analysis showing that our approach effectively fulfills its design objectives.


2020 ◽  
Author(s):  
Emma James ◽  
Gabrielle Ong ◽  
Lisa Henderson ◽  
Aidan J Horner

Event memories are characterised by the holistic retrieval of their constituent elements. Studies show that memory for individual event elements (e.g., person, object, and location) are statistically related to each other, and that the same associative memory structure can be formed by learning all pairwise associations across separated encoding contexts (person-object, person-location, object-location). Counter to previous studies that have shown no differences in holistic retrieval between simultaneously and separately encoded event elements, adults did not show evidence of holistic retrieval from separately encoded event elements when using a similar paradigm adapted for children (Experiment 1). We conducted a further five online experiments to explore the conditions under which holistic retrieval emerges following separated encoding of within-event associations, testing for influences of trial length (Experiment 2), the number of events learned (Experiment 3a), and stimulus presentation format (Experiments 3b, 4a, 4b). Presentation of written words was optimal for integrating elements across encoding trials, whereas the addition of spoken words disrupted integration across separately presented associations. Use of picture stimuli also produced effect sizes smaller than those of previously published research. We discuss the ways in which memory integration processes may be disrupted by these differences in presentation format. The findings have practical implications for the utility of this paradigm across research and learning contexts.


2021 ◽  
Author(s):  
Angélica Acevedo-Mesa ◽  
Rei Monden ◽  
Annelieke Roest ◽  
Jorge Tendeiro ◽  
Judith Rosmalen

Purpose: This study aims to compare the use of sum-scores and person location scores from Item Response Theory (IRT) as outcome measures of Functional Somatic Symptoms (FSS) in an epidemiological study. Method: Data from 1247 participants (60% female) from the Tracking Adolescents' Individual Lives Survey (TRAILS) general population cohort study at the fifth (mean age = 22.2, SD = 0.64) and sixth (mean age = 25.6, SD = 0.6) measurement waves was employed. We fitted the Graded Response Model (GRM) from IRT to the 12 items of the “physical complaints” subscale of the Adult Self-Report (ASR) to calculate item and person location parameters. We performed bootstrapped multiple linear regressions to analyze the relationship between Positive Affect (PA) and FSS using person location scores and compared the results to results obtained using sum-scores. Results: The items “nausea” and “abdominal pain” were most discriminative. ASR sum-scores and person location scores were highly correlated, although the latter captured more variability. Using sum-scores and person location scores to study the association between PA and FSS did not result in relevant differences. Conclusion: Although person location scores capture more variability, we did not find added value in the longitudinal analyses of the association between PA and FSS.


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