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| author | Vasil Zlatanov <v@skozl.com> | 2018-12-10 19:39:42 +0000 |
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| committer | Vasil Zlatanov <v@skozl.com> | 2018-12-10 19:39:42 +0000 |
| commit | fbc302610907099d86e8fdf379b821964b0b8362 (patch) | |
| tree | cee508f81bf25f9789a005a2314259789fb07c7d | |
| parent | 5bdd357102ca539e69f5642d6cc4e5f296bbec61 (diff) | |
| download | vz215_np1915-fbc302610907099d86e8fdf379b821964b0b8362.tar.gz vz215_np1915-fbc302610907099d86e8fdf379b821964b0b8362.tar.bz2 vz215_np1915-fbc302610907099d86e8fdf379b821964b0b8362.zip | |
Fix grammer
| -rwxr-xr-x | report2/paper.md | 6 |
1 files changed, 3 insertions, 3 deletions
diff --git a/report2/paper.md b/report2/paper.md index 7cb28e3..86cf687 100755 --- a/report2/paper.md +++ b/report2/paper.md @@ -3,7 +3,7 @@ ## Probelm Definition -The person re-identification problem presented in this paper requires mtatching +The person re-identification problem presented in this paper requires matching pedestrian images from disjoint cameras by pedestrian detectors. This problem is challenging, as identities captured in photsos are subject to various lighting, pose, blur, background and oclusion from various camera views. This report considers @@ -22,8 +22,8 @@ times. Data is seperated in train, query and gallery sets with `train_idx`, `query_idx` and `gallery_idx` respectively, where the training set has been used to develop the ResNet50 model used for feature extraction. This procedure has allowed the evaluation of distance metric learning techniques on the query and -gallery sets, without an overfit feature set a the set, as it was explicitly -trained on the training set. +gallery sets, with the knowledge that we are not comparing overfitted features, +as they were extracted based on the model derived from the training set. ## Probelm to solve |