In this paper we introduce Context-Sensitive Decision Forests – A new perspective to exploit contextual information in the popular decision forest framework for the object detection problem. They are tree-structured classi\ufb01ers with the ability to access intermediate prediction (here: classi\ufb01cation and regression) information during training and inference time. This intermediate prediction is available for each sample and allows us to develop context-based decision criteria, used for re\ufb01ning the prediction process. In addition, we introduce a novel split criterion which in combination with a priority based way of constructing the trees, allows more accurate regression mode selection and hence improves the current context information. In our experiments, we demonstrate improved results for the task of pedestrian detection on the challenging TUD data set when compared to state-of-the-art methods<\/p>\n","protected":false},"excerpt":{"rendered":"
In this paper we introduce Context-Sensitive Decision Forests – A new perspective to exploit contextual information in the popular decision forest framework for the object detection problem. They are tree-structured classi\ufb01ers with the ability to access intermediate prediction (here: classi\ufb01cation and regression) information during training and inference time. This intermediate prediction is available for each […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13556,13562],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-163512","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-artificial-intelligence","msr-research-area-computer-vision","msr-locale-en_us"],"msr_publishername":"Curran Associates Inc.","msr_edition":"NIPS'12 Proceedings of the 25th International Conference on Neural Information Processing Systems","msr_affiliation":"","msr_published_date":"2012-12-03","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"Neural Information Processing Systems (NIPS)","msr_pages_string":"431-439","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"205737","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","title":"nips2012.pdf","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/nips2012.pdf","id":205737,"label_id":0}],"msr_related_uploader":"","msr_attachments":[{"id":205737,"url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/nips2012.pdf"}],"msr-author-ordering":[{"type":"text","value":"Peter Kontschieder","user_id":0,"rest_url":false},{"type":"text","value":"Samuel Rota Bulo","user_id":0,"rest_url":false},{"type":"user_nicename","value":"antcrim","user_id":31055,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=antcrim"},{"type":"user_nicename","value":"pkohli","user_id":33269,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=pkohli"},{"type":"text","value":"Marcello Pelillo","user_id":0,"rest_url":false},{"type":"text","value":"Horst Bischof","user_id":0,"rest_url":false}],"msr_impact_theme":[],"msr_research_lab":[],"msr_event":[],"msr_group":[],"msr_project":[171004,169659],"publication":[],"video":[],"download":[],"msr_publication_type":"inproceedings","related_content":{"projects":[{"ID":171004,"post_title":"Decision Forests","post_name":"decision-forests","post_type":"msr-project","post_date":"2012-07-25 01:35:22","post_modified":"2017-06-06 12:09:49","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/decision-forests\/","post_excerpt":"Decision Forests for Computer Vision and Medical Image Analysis A. 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