{"id":93,"date":"2023-02-26T04:35:54","date_gmt":"2023-02-26T04:35:54","guid":{"rendered":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s23-teamc1\/?p=93"},"modified":"2023-02-26T04:38:22","modified_gmt":"2023-02-26T04:38:22","slug":"elizabeths-status-report-for-2-25","status":"publish","type":"post","link":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s23-teamc1\/2023\/02\/26\/elizabeths-status-report-for-2-25\/","title":{"rendered":"Elizabeth’s Status Report for 2\/25"},"content":{"rendered":"

Progress<\/strong><\/p>\n

This week I made an OpenCV example using the old Intel RealSense L515 (which should also work for the new Intel Realsense D455). I used Haar cascades (the most common method) to detect faces using the RGB camera that the Intel Realsense device comes with. I used both a frontal and profile cascade (so if it cannot detect a frontal face, it can use the profile face). I also looked into the different methods for face detection. These methods are clearly described in this link<\/a>. I think using OpenCV’s DNN module might be better for our project, as it is more accurate, so I might make an example of that next week. The DNN model might be less accurate based on the training set though, so I will look for a representative training dataset online.\u00a0 In case we want to make the OpenCV process even faster, I found a C++ library<\/a> that runs OpenCV faster by using different SIMD CPU extensions that I might try to use in the future to use if\/after MVP is reached. My example can be found in our team repository<\/a>.<\/p>\n

\"\"<\/p>\n

Schedule<\/strong><\/p>\n

I believe as of now, our progress is on schedule.<\/p>\n

Next Steps<\/strong><\/p>\n

Over the next week, I’ll try to get a DNN example going. More importantly, I will write the Design Review Report with my group members that is due next Friday.<\/p>\n","protected":false},"excerpt":{"rendered":"

Progress This week I made an OpenCV example using the old Intel RealSense L515 (which should also work for the new Intel Realsense D455). I used Haar cascades (the most common method) to detect faces using the RGB camera that the Intel Realsense device comes with. I used both a frontal and profile cascade (so … <\/p>\n

Continue reading “Elizabeth’s Status Report for 2\/25”<\/span><\/a><\/p>\n","protected":false},"author":744,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[8],"tags":[5],"_links":{"self":[{"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s23-teamc1\/wp-json\/wp\/v2\/posts\/93"}],"collection":[{"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s23-teamc1\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s23-teamc1\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s23-teamc1\/wp-json\/wp\/v2\/users\/744"}],"replies":[{"embeddable":true,"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s23-teamc1\/wp-json\/wp\/v2\/comments?post=93"}],"version-history":[{"count":4,"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s23-teamc1\/wp-json\/wp\/v2\/posts\/93\/revisions"}],"predecessor-version":[{"id":110,"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s23-teamc1\/wp-json\/wp\/v2\/posts\/93\/revisions\/110"}],"wp:attachment":[{"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s23-teamc1\/wp-json\/wp\/v2\/media?parent=93"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s23-teamc1\/wp-json\/wp\/v2\/categories?post=93"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s23-teamc1\/wp-json\/wp\/v2\/tags?post=93"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}