1. A process to perform object detection for images from an image sensor, comprising: reusing a 1-dimensional feature from a previously learned weak classifier and selecting a new feature to construct a 2-dimensional feature space; and cross partitioning the 2-dimensional space to learn optimal outputs for instances in each domain within a boosting framework; further comprising aggregating the small block-wise regions into larger ones across both dimensions with discriminability; and learning optimal outputs for instances in each block-wise area independently for a boosting operation.