Abstract

Cascades help make sliding window ob ject detection fast, nevertheless, computational demands remain prohibitive for numerous applications. Currently, evaluation of adjacent windows proceeds inde- pendently; this is suboptimal as detector responses at nearby locations and scales are correlated. We propose to exploit these correlations by tightly coupling detector evaluation of nearby windows. We introduce two opposing mechanisms: detector excitation of promising neighbors to communicate, crosstalk cascades achieve ma jor gains (4-30?speedup) and inhibition of inferior neighbors. By enabling neighboring detectors over cascades evaluated independently at each image location. Combined with recent advances in fast multi-scale feature computation, for which we provide an optimized implementation, our approach runs at 35-65 fps on 640 ?480 images while attaining state-of-the-art accuracy.