Company News

Local Binary Pattern features for pedestrian detection at night/dark environment

Yunyun Cao, Sugiri Pranata, Hirofumi Nishimura
International Conference on Image Processing (ICIP) 2011, 2011.09

Being fast to compute and simple to implement, Local Binary Pattern (LBP) has also shown superior performance in texture classification and face detection. However, it is not well optimized for pedestrian detection. At night/dark environment, pedestrian detection typically needs to overcome problems of low contrast, image blur, and image noise. A novel feature extraction method, consisting of Weighted LBP, Multi-resolution LBP, and Multi-scale LBP, is proposed to solve them. Experimental results show that the proposed method improves upon the basic LBP significantly and outperforms benchmarks such as HOG and CoHOG.

Link: https://ieeexplore.ieee.org/document/6115883

Back

Share

Panasonic Tops the 2018 Nvidia AI City Challenge as First-Place Winner for Anomaly Detection

Panasonic R&D Center Singapore reprises the lead in Face Recognition Technology by notching up a stunning win for Track 2 (Anomaly Detection) in the 2018 Nvidia AI City Challenge .

1-day Design Thinking Workshop @Singapore Polytechnic

We believe creativity is an essential skill for our members trying to make a difference in their work at Panasonic R&D Center Singapore. At this, in collaboration with LWC-S (Live Well Collaborative Singapore) which is based at Singapore Polytechnic, Panasonic R&D Center Singapore organized a one-day design thinking workshop for Panasonic R&D Center Singapore’s members on December 21, 2016.

Panasonic launched a “Panasonic Deep Tech Innovation Challenge” inviting local start-ups to leverage Panasonic’s technology & patents for business creation

Panasonic R&D Center Singapore has launched a Panasonic Deep Tech Innovation Challenge organized by Panasonic, ICMG and ACE. This Challenge…

Panasonic tops MS-Celeb-1M Challenges

Panasonic R&D Center Singapore, in collaboration with the National University of Singapore (NUS), has achieved the No. 1 position in MS-Celeb-1M Challenge 2017 , which is organized by Microsoft, for both Challenge 1 and Challenge 2. The results are in alignment with our mission to promote Panasonic’s outstanding Face Recognition technology worldwide.