People Detection benchmark repository
Results
Author: Bastian Leibe.
Contact university/company: Multimodal Interactive Syst., TU Darmstadt, Germany.
Contact email : leibe@informatik.tu-darmstadt.de
Method name: Implicit Shape Model (ISM) .
Description and pocessing time: The ISM people detector is based on exhaustive search and a holistic person model. It consists in scanning the full image looking for similarities with the chosen person model at multiple scales and locations by local features matching. The chosen person model is based on appearance information using the SIFT features. It has been implemented with C++ and computational cost between 4-7 seconds per frame with 352x288 images. The tests have been performed on a Pentium IV with a CPU frequency of 2.4 GHz and 3GB RAM.
Parameters: Author default parameters here
You can download the people detection results of this method by clicking here.
Results for each video sequence:
Video |
ISM |
1 |
71.4 |
2 |
82.9 |
3 |
75.7 |
4 |
1.0 |
5 |
71.2 |
6 |
34.6 |
7 |
3.0 |
8 |
12.2 |
9 |
65.9 |
10 |
5.5 |
11 |
5.9 |
12 |
76.2 |
13 |
73.6 |
14 |
29.2 |
15 |
20.5 |
16 |
71.5 |
Average AUC |
43.8 |
Ranking |
4.50 |
Results for each background complexity:
Background complexity |
ISM |
Baseline |
76.7 |
Dynamic Background |
36.1 |
Camera Jitter |
18.8 |
Intermittent Object Motion |
22.4 |
Shadow |
54.2 |
Average AUC |
41.6 |
Ranking |
5.00 |
Results for each classification complexity:
Classification complexity |
ISM |
Low |
73.6 |
Medium |
50.5 |
High |
9.5 |
Average AUC |
44.5 |
Ranking |
5.00 |
