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diff --git a/site/content/pages/datasets/duke_mtmc/assets/duke_mtmc_cam5_average_comp.jpg b/site/content/pages/datasets/duke_mtmc/assets/duke_mtmc_cam5_average_comp.jpg
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diff --git a/site/content/pages/datasets/duke_mtmc/index.md b/site/content/pages/datasets/duke_mtmc/index.md
index de1fa14c..c626ef4e 100644
--- a/site/content/pages/datasets/duke_mtmc/index.md
+++ b/site/content/pages/datasets/duke_mtmc/index.md
@@ -2,8 +2,8 @@
status: published
title: Duke Multi-Target, Multi-Camera Tracking
-desc: <span class="dataset-name">Duke MTMC</span> is a dataset of CCTV footage of students at Duke University
-subdesc: Duke MTMC contains over 2 million video frames and 2,000 unique identities collected from 8 cameras at Duke University campus in March 2014
+desc: <span class="dataset-name">Duke MTMC</span> is a dataset of surveillance camera footage of students on Duke University campus
+subdesc: Duke MTMC contains over 2 million video frames and 2,000 unique identities collected from 8 HD cameras at Duke University campus in March 2014
slug: duke_mtmc
cssclass: dataset
image: assets/background.jpg
@@ -15,17 +15,27 @@ authors: Adam Harvey
### sidebar
-+ Collected: March 19, 2014
-+ Cameras: 8
-+ Video Frames: 2,000,000
-+ Identities: Over 2,000
-+ Used for: Person re-identification, <br>face recognition
-+ Sector: Academic
++ Created: 2014
++ Identities: Over 2,700
++ Used for: Face recognition, person re-identification
++ Created by: Computer Science Department, Duke University, Durham, US
+ Website: <a href="http://vision.cs.duke.edu/DukeMTMC/">duke.edu</a>
## Duke Multi-Target, Multi-Camera Tracking Dataset (Duke MTMC)
-(PAGE UNDER DEVELOPMENT)
+[ PAGE UNDER DEVELOPMENT ]
+
+Duke MTMC is a dataset of video recorded on Duke University campus during for the purpose of training, evaluating, and improving *multi-target multi-camera tracking*. The videos were recorded during February and March 2014 and cinclude
+
+Includes a total of 888.8 minutes of video (ind. verified)
+
+"We make available a new data set that has more than 2 million frames and more than 2,700 identities. It consists of 8×85 minutes of 1080p video recorded at 60 frames per second from 8 static cameras deployed on the Duke University campus during periods between lectures, when pedestrian traffic is heavy."
+
+The dataset includes approximately 2,000 annotated identities appearing in 85 hours of video from 8 cameras located throughout Duke University's campus.
+
+![caption: Duke MTMC pixel-averaged image of camera #5 is shown with the bounding boxes for each student drawn in white. (c) Adam Harvey](assets/duke_mtmc_cam5_average_comp.jpg)
+
+According to the dataset authors,
{% include 'map.html' %}
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diff --git a/site/content/pages/datasets/uccs/index.md b/site/content/pages/datasets/uccs/index.md
index 092638c0..b3d16c2e 100644
--- a/site/content/pages/datasets/uccs/index.md
+++ b/site/content/pages/datasets/uccs/index.md
@@ -2,8 +2,8 @@
status: published
title: Unconstrained College Students
-desc: <span class="dataset-name">Unconstrained College Students (UCCS)</span> is a dataset of images ...
-subdesc: The UCCS dataset includes ...
+desc: <span class="dataset-name">Unconstrained College Students (UCCS)</span> is a dataset of long-range surveillance photos of students taken without their knowledge
+subdesc: The UCCS dataset includes 16,149 images and 1,732 identities, is used for face recognition and face detection, and funded was several US defense agences
slug: uccs
cssclass: dataset
image: assets/background.jpg
@@ -15,16 +15,22 @@ authors: Adam Harvey
### sidebar
-+ Collected: TBD
-+ Published: TBD
-+ Images: TBD
-+ Faces: TBD
++ Published: 2018
++ Images: 16,149
++ Identities: 1,732
++ Used for: Face recognition, face detection
++ Created by: Unviversity of Colorado Colorado Springs (US)
++ Funded by: ODNI, IARPA, ONR MURI, Amry SBIR, SOCOM SBIR
++ Website: <a href="https://vast.uccs.edu/Opensetface/">vast.uccs.edu</a>
## Unconstrained College Students ...
(PAGE UNDER DEVELOPMENT)
+![caption: The pixel-average of all Uconstrained College Students images is shown with all 51,838 face annotations. (c) Adam Harvey](assets/uccs_mean_bboxes_comp.jpg)
+
+
{% include 'map.html' %}
{% include 'chart.html' %}
@@ -36,7 +42,6 @@ authors: Adam Harvey
{% include 'citations.html' %}
-![Bounding box visualization](assets/uccs_bboxes_grayscale.jpg)
### Research Notes
@@ -55,4 +60,15 @@ The more recent UCCS version of the dataset received funding from [^funding_uccs
[^funding_sb]: Sapkota, Archana and Boult, Terrance. "Large Scale Unconstrained Open Set Face Database." 2013.
-[^funding_uccs]: Günther, M. et. al. "Unconstrained Face Detection and Open-Set Face Recognition Challenge," 2018. Arxiv 1708.02337v3. \ No newline at end of file
+[^funding_uccs]: Günther, M. et. al. "Unconstrained Face Detection and Open-Set Face Recognition Challenge," 2018. Arxiv 1708.02337v3.
+
+
+" In most face detection/recognition datasets, the majority of images are “posed”, i.e. the subjects know they are being photographed, and/or the images are selected for publication in public media. Hence, blurry, occluded and badly illuminated images are generally uncommon in these datasets. In addition, most of these challenges are close-set, i.e. the list of subjects in the gallery is the same as the one used for testing.
+
+This challenge explores more unconstrained data, by introducing the new UnConstrained College Students (UCCS) dataset, where subjects are photographed using a long-range high-resolution surveillance camera without their knowledge. Faces inside these images are of various poses, and varied levels of blurriness and occlusion. The challenge also creates an open set recognition problem, where unknown people will be seen during testing and must be rejected.
+
+With this challenge, we hope to foster face detection and recognition research towards surveillance applications that are becoming more popular and more required nowadays, and where no automatic recognition algorithm has proven to be useful yet.
+
+UnConstrained College Students (UCCS) Dataset
+
+The UCCS dataset was collected over several months using Canon 7D camera fitted with Sigma 800mm F5.6 EX APO DG HSM lens, taking images at one frame per second, during times when many students were walking on the sidewalk. " \ No newline at end of file