{"id":353,"date":"2015-10-01T08:25:46","date_gmt":"2015-10-01T08:25:46","guid":{"rendered":"http:\/\/project.dke.maastrichtuniversity.nl\/RAI\/?page_id=353"},"modified":"2021-05-17T08:16:41","modified_gmt":"2021-05-17T08:16:41","slug":"datasets","status":"publish","type":"page","link":"https:\/\/project.dke.maastrichtuniversity.nl\/RAI\/?page_id=353","title":{"rendered":"Datasets and Demos"},"content":{"rendered":"\n<h4 class=\"wp-block-heading\">Testing our abnormal behavior detection algorithms in the Hospital of Pecs (Hu)<\/h4>\n\n\n\n<p class=\"wp-block-paragraph\">Together with the ICT4Life project consortium, RAI tested the real-time abnormal behavior detection system in the Hospital of Pecs (Hungary). Our system aims to support medical professionals in the early detection, and daily monitoring of wandering\/confusion and agitation states.<\/p>\n\n\n\n<figure class=\"wp-block-embed-youtube wp-block-embed is-type-video is-provider-youtube wp-embed-aspect-4-3 wp-has-aspect-ratio\"><div class=\"wp-block-embed__wrapper\">\n<iframe loading=\"lazy\"  id=\"_ytid_82317\"  width=\"480\" height=\"360\"  data-origwidth=\"480\" data-origheight=\"360\" src=\"https:\/\/www.youtube.com\/embed\/YdrOe2wTYU4?enablejsapi=1&#038;autoplay=0&#038;cc_load_policy=0&#038;cc_lang_pref=&#038;iv_load_policy=1&#038;loop=0&#038;rel=1&#038;fs=1&#038;playsinline=0&#038;autohide=2&#038;theme=dark&#038;color=red&#038;controls=1&#038;disablekb=0&#038;\" class=\"__youtube_prefs__  epyt-is-override  no-lazyload\" title=\"YouTube player\"  allow=\"fullscreen; accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen data-no-lazy=\"1\" data-skipgform_ajax_framebjll=\"\"><\/iframe>\n<\/div><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n<p><strong>Personality in a nonsocial context Dataset<\/strong><\/p>\n<p><a href=\"https:\/\/project.dke.maastrichtuniversity.nl\/RAI\/wp-content\/uploads\/2018\/10\/dataset_sample_img.png\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-982\" src=\"https:\/\/project.dke.maastrichtuniversity.nl\/RAI\/wp-content\/uploads\/2018\/10\/dataset_sample_img.png\" alt=\"\" width=\"1375\" height=\"436\" srcset=\"https:\/\/project.dke.maastrichtuniversity.nl\/RAI\/wp-content\/uploads\/2018\/10\/dataset_sample_img.png 1375w, https:\/\/project.dke.maastrichtuniversity.nl\/RAI\/wp-content\/uploads\/2018\/10\/dataset_sample_img-300x95.png 300w, https:\/\/project.dke.maastrichtuniversity.nl\/RAI\/wp-content\/uploads\/2018\/10\/dataset_sample_img-768x244.png 768w, https:\/\/project.dke.maastrichtuniversity.nl\/RAI\/wp-content\/uploads\/2018\/10\/dataset_sample_img-1024x325.png 1024w, https:\/\/project.dke.maastrichtuniversity.nl\/RAI\/wp-content\/uploads\/2018\/10\/dataset_sample_img-624x198.png 624w\" sizes=\"auto, (max-width: 1375px) 100vw, 1375px\" \/><\/a><\/p>\n<p><span class=\"fontstyle0\">We introduce a novel dataset for behavior understanding and personality recognition in a nonsocial context. Forty-six participants were recorded in an unconstrained indoor space, related to a smart home environment, performing six tasks resembling Activities of Daily\u00a0Living (ADL)<\/span>\u00a0.\u00a0\u00a0<span class=\"fontstyle0\">During the experiment, personality scores\u00a0were collected using self-assessment questionnaire (BFI-10).<\/span><\/p>\n<p><blockquote class=\"wp-embedded-content\" data-secret=\"nswgwfvsIA\"><a href=\"https:\/\/project.dke.maastrichtuniversity.nl\/personality\/\">Personality in a nonsocial context  Dataset<\/a><\/blockquote><iframe loading=\"lazy\" class=\"wp-embedded-content\" sandbox=\"allow-scripts\" security=\"restricted\" style=\"position: absolute; clip: rect(1px, 1px, 1px, 1px);\" title=\"&#8220;Personality in a nonsocial context  Dataset&#8221; &#8212; \" src=\"https:\/\/project.dke.maastrichtuniversity.nl\/personality\/?embed=true#?secret=ALDmoBKUG3#?secret=nswgwfvsIA\" data-secret=\"nswgwfvsIA\" width=\"500\" height=\"282\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\"><\/iframe><\/p>\n<p>\u00a0<\/p>\n<p><strong>RAI conducting research in novel learning paradigms<\/strong><\/p>\n<p>RAI is leading the machine intelligence work-package in MaTHiSiS. For this, RAI conducts research on intelligent tools for learning, based on automatic human emotion recognition and personalization of the learning procedure, based on AI:<\/p>\n<p>\u00a0<\/p>\n<iframe loading=\"lazy\"  id=\"_ytid_19214\"  width=\"480\" height=\"360\"  data-origwidth=\"480\" data-origheight=\"360\" src=\"https:\/\/www.youtube.com\/embed\/TonwoAOb0cc?enablejsapi=1&autoplay=0&cc_load_policy=0&cc_lang_pref=&iv_load_policy=1&loop=0&rel=1&fs=1&playsinline=0&autohide=2&theme=dark&color=red&controls=1&disablekb=0&\" class=\"__youtube_prefs__  no-lazyload\" title=\"YouTube player\"  allow=\"fullscreen; accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen data-no-lazy=\"1\" data-skipgform_ajax_framebjll=\"\"><\/iframe>\n<p>\u00a0<\/p>\n<p><strong>RAI developing AI techniques for the elderly<\/strong><\/p>\n<p>RAI, as part of the ICT4Life project, is conducting research in Ambient Assisted Living, using computer vision. The latest project is in anomaly detection in indoor activities, with an outer call to provide the caregivers with timely messages and warnings:<\/p>\n<p>\u00a0<\/p>\n<iframe loading=\"lazy\"  id=\"_ytid_47953\"  width=\"480\" height=\"270\"  data-origwidth=\"480\" data-origheight=\"270\" src=\"https:\/\/www.youtube.com\/embed\/8hGOTFhhocI?enablejsapi=1&autoplay=0&cc_load_policy=0&cc_lang_pref=&iv_load_policy=1&loop=0&rel=1&fs=1&playsinline=0&autohide=2&theme=dark&color=red&controls=1&disablekb=0&\" class=\"__youtube_prefs__  no-lazyload\" title=\"YouTube player\"  allow=\"fullscreen; accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen data-no-lazy=\"1\" data-skipgform_ajax_framebjll=\"\"><\/iframe>\n<p>\u00a0<\/p>\n<p><strong>TurtleBot learning application in MaTHiSiS project<\/strong><\/p>\n<p>UM has developed several applications to be using in the context of <a href=\"http:\/\/www.mathisis-project.eu\/\">MaTHiSiS<\/a> platform. These applications will be used in learning environments by chidren with and without special needs (namely, Autism Spectrum Disorder and Profound and Multiple Learning Disabilities).<\/p>\n<p>You can see the robot application during one of the tests performed in DKE facilities:<\/p>\n<p>\u00a0<\/p>\n<p>\u00a0<\/p>\n<center>\n<p>\u00a0<\/p>\n<p><iframe loading=\"lazy\" title=\"TurtleBot learning application in MaTHiSiS project\" width=\"513\" height=\"385\" src=\"https:\/\/www.youtube.com\/embed\/m8-BYzpeN_g?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen><\/iframe><\/p>\n<p>\u00a0<\/p>\n<p>\u00a0<\/p>\n<p>\u00a0<\/p>\n<p>\u00a0<\/p>\n<\/center>\n<p>\u00a0<\/p>\n<p>\u00a0<\/p>\n<hr \/>\n<p><strong>Abnormal behavior Detector in ICT4Life Platform <\/strong><\/p>\n<p>We present a realtime algorithm to detect common Alzheimer&#8217;s symptoms such as confused and repetitive behaviors.\u00a0Our model takes as input Kinect video data as well as ambient sensors and produces a behavior classification output.<\/p>\n<p>In this demo we discriminate between normal daily activities and common behavioral symptoms of Alzheimer &#8216;s disease.<\/p>\n<p>More information at: <a href=\"http:\/\/www.ict4life.eu\">www.ict4life.eu<\/a><\/p>\n<p><iframe loading=\"lazy\" title=\"Abnormal Behavior Detector in ICT4Life Platform\" width=\"640\" height=\"360\" src=\"https:\/\/www.youtube.com\/embed\/quoKeF1hC-8?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen><\/iframe><\/p>\n<p>\u00a0<\/p>\n<hr \/>\n<p>The <strong>Head Pose &#8211; Eye Gaze dataset<\/strong>\u00a0 <strong>(HPEG)<\/strong> has been built in order to assist in research related to human gaze recognition, with monocular, uncalibrated systems, under the constraint of free head and eye gaze rotations.<\/p>\n<p>You can download <a href=\"http:\/\/www.image.ece.ntua.gr\/~stiast\/HPEG\" target=\"_blank\" rel=\"noopener noreferrer\">HPEG<\/a> (Head Pose &amp; Eye Gaze dataset) from <a href=\"http:\/\/www.image.ece.ntua.gr\/~stiast\/HPEG\" target=\"_blank\" rel=\"noopener noreferrer\">here<\/a>. The dataset consists of two sessions: one just head pose of people moving freely their heads, and one combining both cues (Head Pose and Eye Gaze). It was recorded in indoor conditions, with a complex background and intense human action taking place in some of the sequences. For more details, please, read the paper found in this <a href=\"http:\/\/www.image.ece.ntua.gr\/php\/pub_details.php?code=611\" target=\"_blank\" rel=\"noopener noreferrer\">paper<\/a>.<\/p>\n<p>The dataset can be freely downloaded and used for research purposes, and provided that any work done with the dataset should cite the\u00a0following work:<\/p>\n<p>Asteriadis, Stylianos, Dimitris Soufleros, Kostas Karpouzis, and Stefanos Kollias. &#8220;A natural head pose and eye gaze dataset.&#8221; In <i>Proceedings of the International Workshop on Affective-Aware Virtual Agents and Social Robots<\/i>, p. 1. ACM, 2009.<\/p>\n<p><a href=\"http:\/\/dke.maastrichtuniversity.nl\/stelios.asteriadis\/wp-content\/uploads\/2015\/04\/HPEG.png\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-90\" src=\"http:\/\/dke.maastrichtuniversity.nl\/stelios.asteriadis\/wp-content\/uploads\/2015\/04\/HPEG.png\" alt=\"HPEG\" width=\"383\" height=\"138\" \/><\/a><\/p>\n<p>\u00a0<\/p>\n<hr \/>\n<p>We present the\u00a0<strong><em>Platformer Experience\u00a0Dataset<\/em>\u00a0(PED)\u00a0\u2014 the first open-access game\u00a0experience corpus<\/strong> \u2014 that contains multiple modalities\u00a0of user\u00a0data\u00a0of Super Mario\u00a0Bros players. The open-access database aims to be\u00a0used for player experience capture through context based (i.e. game content), behavioral and visual recordings of platform game players. In addition, the database contains demographical data of the players and self-reported annotations of experience in two forms:\u00a0<strong>ratings<\/strong>\u00a0and\u00a0<strong>ranks<\/strong>. PED opens up the way to desktop and console games that use video from web cameras and visual sensors and offer\u00a0possibilities for holistic player experience modeling approaches that can, in turn, yield richer game personalization.<\/p>\n<p>The dataset is made publicly available\u00a0<a href=\"http:\/\/institutedigitalgames.com\/PED\/\">here\u00a0<\/a> and we encourage researchers to use it for testing their own\u00a0player experience detectors.<\/p>\n<p>The dataset is presented in the following paper (please\u00a0<em>cite<\/em>\u00a0our work if you use the dataset for your research):<\/p>\n<ul>\n<li>Karpouzis, G. Yannakakis, N Shaker, S. Asteriadis.\u00a0<a href=\"https:\/\/www.researchgate.net\/profile\/Stylianos_Asteriadis\/publication\/280931694_The_Platformer_Experience_Dataset\/links\/55cc4fc508aeb975674c8684.pdf\">The Platfo<\/a><a href=\"https:\/\/www.researchgate.net\/profile\/Stylianos_Asteriadis\/publication\/280931694_The_Platformer_Experience_Dataset\/links\/55cc4fc508aeb975674c8684.pdf\">rmer Experience Dataset<\/a>, Sixth Affective Computing and Intelligent Interaction (ACII) Conference, Xi\u2019an, China, 21-24 September, 2015.<\/li>\n<\/ul>\n<p><a href=\"http:\/\/dke.maastrichtuniversity.nl\/stelios.asteriadis\/wp-content\/uploads\/2015\/04\/PED.png\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-146\" src=\"http:\/\/dke.maastrichtuniversity.nl\/stelios.asteriadis\/wp-content\/uploads\/2015\/04\/PED.png\" alt=\"PED\" width=\"432\" height=\"203\" \/><\/a><\/p>","protected":false},"excerpt":{"rendered":"<p>Testing our abnormal behavior detection algorithms in the Hospital of Pecs (Hu) Together with the ICT4Life project consortium, RAI tested the real-time abnormal behavior detection system in the Hospital of Pecs (Hungary). Our system aims to support medical professionals in the early detection, and daily monitoring of wandering\/confusion and agitation states. Personality in a nonsocial&#8230;  <a class=\"excerpt-read-more\" href=\"https:\/\/project.dke.maastrichtuniversity.nl\/RAI\/?page_id=353\" title=\"ReadDatasets and Demos\">Read more &raquo;<\/a><\/p>\n","protected":false},"author":6,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-353","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/project.dke.maastrichtuniversity.nl\/RAI\/index.php?rest_route=\/wp\/v2\/pages\/353","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/project.dke.maastrichtuniversity.nl\/RAI\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/project.dke.maastrichtuniversity.nl\/RAI\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/project.dke.maastrichtuniversity.nl\/RAI\/index.php?rest_route=\/wp\/v2\/users\/6"}],"replies":[{"embeddable":true,"href":"https:\/\/project.dke.maastrichtuniversity.nl\/RAI\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=353"}],"version-history":[{"count":22,"href":"https:\/\/project.dke.maastrichtuniversity.nl\/RAI\/index.php?rest_route=\/wp\/v2\/pages\/353\/revisions"}],"predecessor-version":[{"id":1261,"href":"https:\/\/project.dke.maastrichtuniversity.nl\/RAI\/index.php?rest_route=\/wp\/v2\/pages\/353\/revisions\/1261"}],"wp:attachment":[{"href":"https:\/\/project.dke.maastrichtuniversity.nl\/RAI\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=353"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}