PETS 2009 Benchmark Data

Overview

The datasets are multisensor sequences containing different crowd activities.

Dataset S0: Training Data Size of Dataset
Backgound Set 1.8 GB
City Center 1.8 GB
Regular Flow 1.3 GB



Dataset S1: Person Count and Density Estimation Elements Difficulty
S1.L1 walking medium density crowd, overcast Level 1
Task: Count the number of people in R0 for each frame of the sequence in View 1 only. As a secondary challenge the crowd density in regions R1 and R2 can also be reported (mapped to ground plane occupancy, possibly using multiple views).
S1.L2 walking high density crowd, overcast Level 2
Task: The task related to timestamp 14-06 is to estimate the crowd density in Region R1 and R2 at each frame of the sequence. The designated task for the sequence Time_14-31 is to determine both the total number of people entering through the brown line from the left side AND the total number of people exiting from purple and red lines, shown in the opposite figure, throughout the whole sequence. The coordinates of the entry and exit lines are given below for reference.
S1.L3 running medium density crowd, bright sunshine and shadows Level 3
Task: This scenario contains a crowd of people who, on reaching a point in the scene, begin to run. The task is to measure the crowd density in Region R1 at each frame of the sequence.


Dataset S2: People Tracking Elements Difficulty
S2.L1 walking sparse crowd Level 1
Task: Track all of the individuals in the sequence. If you undertake monocular tracking only, report the 2D bounding box location for each individual in the view used; if two or more views are processed, report the 2D bounding box location for each individual as back projected into View_002 using the camera calibration parameters provided (this equates to a leave-one-out validation). Note the origin (0,0) of the image is assumed top-left. Validation will be performed using manually labelled ground truth.
S2.L2 walking medium density crowd Level 2
Task: Track the individuals marked A and B (see figure) in the sequence and provide 2D bounding box locations of the individuals in View_002 which will be validated using manually labelled ground truth. Note the origin (0,0) of the image is assumed top-left. Note that individual B exits the field of view and returns toward the end of the sequence.
S2.L3 walking dense crowd Level 3
Task: Track the individuals marked A and B in the sequence and provide 2D bounding box information in View_002 for each individual which will be validated using manually labelled ground truth.


Dataset S3: Flow Analysis and Event Recognition Elements Difficulty
S3 Multiple Flows dense crowd, running Level 2
Task: Detect and estimate the multiple flows in the provided sequences, mapped onto the ground plane as a occupancy map flow. Further details of the exact task requirements are contained under Author Instructions. These would be compared with ground truth optical flow of major flows in the sequences on the ground plane.
S3 Event Recognition dense crowd Level 3
Task: This dataset contains different crowd activities and the task is to provide a probabilistic estimation of each of the following events: walking, running, evacuation (rapid dispersion), local dispersion, crowd formation and splitting at different time instances. Furthermore, we are interested in systems that can identify the start and end of the events as well as transitions between them.

For more information regarding the PETS 2009 data please visit their website at http://winterpets09.net