|
|
Datasets: Motion Capture
|
- HumanEVA dataset for benchmarking 3D human pose recovery. The dataset, provided by the Brown University, contains 7 calibrated video sequences that are synchronized with 3D body poses obtained from a motion capture system. The dataset contains 4 subjects performing 6 common actions (e.g. walking, jogging, gesturing, etc.). The error metrics for computing error in 2D and 3D pose are provided to participants. The dataset contains training, validation and testing (with withheld ground truth) sets.
- CMU motion capture database. 2605 trials in 6 motion categories (23 subcategories).
- HDM05 Mocap Database from the University of Bonn. approxiimately 70 motion classes each performed 10-50 times, for a total of 1500 motion clips and three hours of data.
- Mega MoCap V2 (commerical product). Motion capture library of 500 motions
.
|
|
Datasets: Other
|
- DaimlerChrysler pedestrian classification benchmark. Large dataset (4000 pedestrian and 5000 non-pedestrian samples of size 18x36, plus 1200 additional images) for benchmarking classification methods.
- CMU pose, illumination and expression (PIE) database A database of 41,368 images of 68 people. Each person imaged under 13 different poses, 43 different illumination conditions and with 4 different expressions.
- Video database of moving faces and people. Univ. of Texas (Dallas) database for testing algorithms for face and person recognition, head/eye tracking, and computer graphics modeling of natural human motions. For each person there are nine static facial mug shots and a series of video streams. Complete data sets are available for 284 subjects and duplicate data sets, taken subsequent to the original set, are available for 229 subjects.
|
|
