{"id":166913,"date":"2014-09-07T00:00:00","date_gmt":"2014-09-07T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/enabling-physical-analytics-in-retail-stores-using-smart-glasses\/"},"modified":"2018-10-16T21:14:52","modified_gmt":"2018-10-17T04:14:52","slug":"enabling-physical-analytics-in-retail-stores-using-smart-glasses","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/enabling-physical-analytics-in-retail-stores-using-smart-glasses\/","title":{"rendered":"Enabling Physical Analytics in Retail Stores Using Smart Glasses"},"content":{"rendered":"<div class=\"asset-content\">\n<p>We consider the problem of tracking physical browsing by users in indoor spaces such as retail stores. Analogous to online browsing, where users choose to go to certain webpages, dwell on a subset of pages of interest to them, and click on links of interest while ignoring others, we can draw parallels in the physical setting, where a user might &#8220;walk&#8221; purposefully to a section of interest, &#8220;dwell&#8221; there for a while, &#8220;gaze&#8221; at specific items, and &#8220;reach out&#8221; for the ones that they wish to examine more closely and possibly purchase.<\/p>\n<p>As our first contribution, we design techniques to track each of these elements of physical browsing using a combination of a first-person vision enabled by smart glasses, and inertial sensing using both the glasses and a smartphone. We address key challenges, including energy efficiency by using the less expensive inertial sensors. Second, during gazing, we present a method for identifying the item(s) within view that the user is likely to focus on based on measuring the orientation of the user&#8217;s head.<\/p>\n<p>Finally, unlike in the online context, where every webpage is just a click away, proximity is important in the physical browsing setting. To enable the tracking of nearby items, even if outside the field of view, we use data gathered from smart-glasses-enabled users to infer the product layout using a novel technique called AutoLayout. Further, we show how such inferences made from a small population of smart-glasses-enabled users could aid in tracking the physical browsing by the many smartphone-only users.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>We consider the problem of tracking physical browsing by users in indoor spaces such as retail stores. Analogous to online browsing, where users choose to go to certain webpages, dwell on a subset of pages of interest to them, and click on links of interest while ignoring others, we can draw parallels in the physical [&hellip;]<\/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":[13547],"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-166913","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-systems-and-networking","msr-locale-en_us"],"msr_publishername":"ACM - Association for Computing Machinery","msr_edition":"ACM Mobicom 2014","msr_affiliation":"","msr_published_date":"2014-09-07","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"ACM Mobicom 2014","msr_pages_string":"","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":"204660","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","title":"ThirdEye-Mobicom2014.PDF","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/ThirdEye-Mobicom2014.pdf","id":204660,"label_id":0}],"msr_related_uploader":"","msr_attachments":[{"id":204660,"url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/ThirdEye-Mobicom2014.pdf"}],"msr-author-ordering":[{"type":"text","value":"Swati Rallapalli","user_id":0,"rest_url":false},{"type":"text","value":"Aishwarya Ganesan","user_id":0,"rest_url":false},{"type":"user_nicename","value":"krchinta","user_id":32577,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=krchinta"},{"type":"user_nicename","value":"padmanab","user_id":33180,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=padmanab"},{"type":"text","value":"Lili Qiu","user_id":0,"rest_url":false},{"type":"user_nicename","value":"t-aigane","user_id":0,"rest_url":false}],"msr_impact_theme":[],"msr_research_lab":[199562],"msr_event":[],"msr_group":[144725,144939],"msr_project":[171101],"publication":[],"video":[],"download":[],"msr_publication_type":"inproceedings","related_content":{"projects":[{"ID":171101,"post_title":"Phytics: Physical Analytics","post_name":"phytics-physical-analytics","post_type":"msr-project","post_date":"2013-02-18 00:54:57","post_modified":"2020-12-10 19:56:31","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/phytics-physical-analytics\/","post_excerpt":"The goal of the Physical Analytics project, or Phytics, is to perform analytics on the physical actions of users. Such analytics would be valuable in a variety of contexts where the design of a physical space is intertwined with how users use the space, e.g., to understand the behaviour of shoppers in mall or a store, which might be indicative of their interests; to fine-tune the layout of services in an airport or a train&hellip;","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/171101"}]}}]},"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/166913"}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-research-item"}],"version-history":[{"count":2,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/166913\/revisions"}],"predecessor-version":[{"id":534164,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/166913\/revisions\/534164"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=166913"}],"wp:term":[{"taxonomy":"msr-content-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-content-type?post=166913"},{"taxonomy":"msr-research-highlight","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-highlight?post=166913"},{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=166913"},{"taxonomy":"msr-publication-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-publication-type?post=166913"},{"taxonomy":"msr-product-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-product-type?post=166913"},{"taxonomy":"msr-focus-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-focus-area?post=166913"},{"taxonomy":"msr-platform","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-platform?post=166913"},{"taxonomy":"msr-download-source","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-download-source?post=166913"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=166913"},{"taxonomy":"msr-post-option","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-post-option?post=166913"},{"taxonomy":"msr-field-of-study","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-field-of-study?post=166913"},{"taxonomy":"msr-conference","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-conference?post=166913"},{"taxonomy":"msr-journal","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-journal?post=166913"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=166913"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=166913"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}