MuseumVisitors: A dataset for pedestrian and group detection, gaze estimation and behavior understanding

Bartoli, Federico; Lisanti, Giuseppe; Seidenari, Lorenzo; Karaman, Svebor; Bimbo, Alberto Del

doi:10.1109/cvprw.2015.7301279

Cited by 11 publications

(4 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…e dataset contains a small number of images and is intended to address the problem of image search (e.g., recognizing a painting). In [3], is presented a dataset acquired inside the National Museum of Bargello in Florence. e dataset (acquired by 3 xed IPcameras) is intended for pedestrian and group detection, gaze estimation and behavior understanding.…”

Section: Location-based Recommendationmentioning

confidence: 99%

“…To gather information about the visitors (i.e., what they see and where they are) in an automated way, past works have employed xed cameras and classic "third person vision" algorithms to detect, track, count people and estimate their gaze [3]. However, systems based on third person vision are capped by several limitations: 1) xed cameras need to be installed in the cultural site and this is not always possible, 2) the xed viewpoint of third person cameras makes it di cult to estimate what the visitors are looking at (e.g., ambiguity on estimation of what people see), 3) xed cameras are easily a ected by occlusion and people re-identi cation problems (e.g., di culties to follow a person from a room to another), 3) the system has to work for several visitors at a time, making it di cult to pro le them and to adapt its functioning to their speci c needs (e.g., personal recommendation). Moreover, systems based on third person vision cannot easily communicate to the visitor in order to "augment his visit" providing information on the observed cultural object or by recommending what to see next.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Egocentric Visitors Localization in Cultural Sites

Ragusa

Furnari

Battiato

et al. 2019

J. Comput. Cult. Herit.

View full text Add to dashboard Cite

We consider the problem of localizing visitors in a cultural site from egocentric ( rst person) images. Localization information can be useful both to assist the user during his visit (e.g., by suggesting where to go and what to see next) and to provide behavioral information to the manager of the cultural site (e.g., how much time has been spent by visitors at a given location? What has been liked most?). To tackle the problem, we collected a large dataset of egocentric videos using two cameras: a head-mounted HoloLens device and a chest-mounted GoPro. Each frame has been labeled according to the location of the visitor and to what he was looking at. e dataset is freely available in order to encourage research in this domain. e dataset is complemented with baseline experiments performed considering a state-of-the-art method for location-based temporal segmentation of egocentric videos. Experiments show that compelling results can be achieved to extract useful information for both the visitor and the site-manager.

show abstract

Section: Location-based Recommendationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Egocentric Visitors Localization in Cultural Sites

Ragusa

Furnari

Battiato

et al. 2019

J. Comput. Cult. Herit.

View full text Add to dashboard Cite

show abstract

“…As an additional contribution, we allow for multi-person gaze estimation within the RT-GENE framework [13]. Multiperson gaze estimation is beneficial for a range of scenarios, including the detection of attention in group scenarios [6].…”

Section: Multi-person Gaze Estimationmentioning

confidence: 99%

RT-BENE: A Dataset and Baselines for Real-Time Blink Estimation in Natural Environments

Cortacero

Fischer

Demiris

2019

2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)

View full text Add to dashboard Cite

In recent years gaze estimation methods have made substantial progress, driven by the numerous application areas including human-robot interaction, visual attention estimation and foveated rendering for virtual reality headsets. However, many gaze estimation methods typically assume that the subject's eyes are open; for closed eyes, these methods provide irregular gaze estimates. Here, we address this assumption by first introducing a new open-sourced dataset with annotations of the eye-openness of more than 200,000 eye images, including more than 10,000 images where the eyes are closed. We further present baseline methods that allow for blink detection using convolutional neural networks. In extensive experiments, we show that the proposed baselines perform favourably in terms of precision and recall. We further incorporate our proposed RT-BENE baselines in the recently presented RT-GENE gaze estimation framework where it provides a real-time inference of the openness of the eyes. We argue that our work will benefit both gaze estimation and blink estimation methods, and we take steps towards unifying these methods.

show abstract

“…46. Sample frames from the MuseumVisitor dataset.First and second row show indivisual and groups from the three camera installed in a museum (image source[48]).…”

mentioning

confidence: 99%

Multimedia Datasets for Anomaly Detection: A Review

Kumari¹,

Bedi²,

Saini³

2021

Preprint

View full text Add to dashboard Cite

Audio or video anomaly datasets play a crucial role in automated surveillance. The range of applications expand from outlier object/ situation detection to the detection of lifethreatening events. This research area has been active for more than 1.5 decades, and consequently, more and more datasets dedicated to anomalous actions and object detection have been created. Making use of these public anomaly datasets enable researchers to compare various anomaly detection frameworks with the same input data. This survey aims to address the lack of a comprehensive comparison and analysis of public datasets for audio, video, and audio-visual based anomaly detection. It also assists in selecting the best dataset for bench-marking frameworks. Additionally, we discuss gaps in the existing dataset and future direction insights toward developing multimodal anomaly detection datasets.

show abstract

MuseumVisitors: A dataset for pedestrian and group detection, gaze estimation and behavior understanding

Cited by 11 publications

References 32 publications

Egocentric Visitors Localization in Cultural Sites

Egocentric Visitors Localization in Cultural Sites

RT-BENE: A Dataset and Baselines for Real-Time Blink Estimation in Natural Environments

Multimedia Datasets for Anomaly Detection: A Review

Contact Info

Product

Resources

About