We propose a feature extraction pipeline namely Difference Matrix Projection (DMP)for pedestrian detection. The goal is to design an effective feature set that can be efficiently computed. Our feature consists of pixel differences at different scales and orientations coupled with average pooling and block normalization. We develop a formulation that computes the difference maps and local average using global image projection instead of an iterative filtering. As a result, the computations can be expressed by analytic equations in terms of the input image. The projection matrices are pre-constructed, so they are readily applied to the image for feature extraction. Experiment results on the Daimler Chrysler (Daimler-CB) and NICTA pedestrian datasets show encouraging results, especially for low-resolution samples.
|Title of host publication||2018 IEEE 4th International Conference on Identity, Security, and Behavior Analysis, ISBA 2018|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||6|
|Publication status||Published - 2018 Mar 9|
|Event||4th IEEE International Conference on Identity, Security, and Behavior Analysis, ISBA 2018 - Singapore, Singapore|
Duration: 2018 Jan 11 → 2018 Jan 12
|Name||2018 IEEE 4th International Conference on Identity, Security, and Behavior Analysis, ISBA 2018|
|Other||4th IEEE International Conference on Identity, Security, and Behavior Analysis, ISBA 2018|
|Period||18/1/11 → 18/1/12|
Bibliographical noteFunding Information:
This research was supported by Basic Science Research Program through the National Research Founda- tion of Korea (NRF) funded by the Ministry of Education, Science and Technology (Grant number: NRF-2015R1D1A1A09061316).
© 2018 IEEE.
All Science Journal Classification (ASJC) codes
- Computer Networks and Communications
- Computer Vision and Pattern Recognition
- Safety, Risk, Reliability and Quality
- Behavioral Neuroscience
- Social Sciences (miscellaneous)