| Paper: | MA-P4.2 |
| Session: | Biometrics II: Human Activity, Gait, Gaze Analysis |
| Time: | Monday, September 17, 09:50 - 12:30 |
| Presentation: |
Poster
|
| Title: |
ABNORMAL ACTIVITY RECOGNITION IN OFFICE BASED ON R TRANSFORM |
| Authors: |
Ying Wang; National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences | | |
| | Kaiqi Huang; National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences | | |
| | Tieniu Tan; National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences | | |
| Abstract: |
This paper introduces an abnormal activity recognition method based on a new feature descriptor for human silhouette. For a binary human silhouette, an extended radon transform, R transform, is employed to represent low-level features. The information that the initial silhouette carries is transformed in a compact way preserving important spatial information of the activities. Then a set of HMMs based on the features extracted by our method are trained to recognize abnormal activities. Experiments have proved the accuracy and efficiency of the proposed method, and the comparison with Fourier descriptor illustrates its robustness to disjoint shape and shape with holes. |
