Figure 6.

Results for the crossing vs. stopping classification task (${\mathcal{C}}_c$), using GT (ground truth) pedestrian BBs (Bounding Box), a time sliding window of 10, the RBF-SVM classifier and 16–8 as a trade-off for setting positive and negative frames during training. ’Cro’ curve means applied to testing sequences of crossing, ’Sto’ curve means applied to testing sequences of stopping. Note that the frames from the stopping sequences are rightly classified if ${\mathcal{C}}_c>0.20$, while for the crossing sequences those are the wrongly classified. (a) classification probability (mean as curves, standard deviation as colored areas); (b) predictability for ${\mathcal{C}}_c$ with threshold $0.20$.