Improving pedestrian detection with selective gradient self-similarity feature
We propose the selective gradient self-similarity (SGSS) feature. SGSS captures pairwise similarity patterns of local gradient distributions. SGSS is a mid-level feature on top of HOG and is complementary to HOG. Addition of SGSS gives a significant boost to pedestrian detection accuracy. The AdaBoost-based cascade with HOG-SGSS outperforms the linear SVM/HIKSVM.
pedestrian detection self-similarity cascade contour description feature selection