Abstract:

This paper proposes a novel image modeling scheme for object detection and localization. Object appearance is modeled by the joint distribution of k-tuple salient point feature vectors which are factorized component-wise after an independent component analysis (ICA). Also, we propose a distance-sensitive histograming technique for capturing spatial dependencies. The advantages over existing techniques include the ability to model non-rigid objects (at the expense of modeling accuracy) and the flexibility in modeling spatial relationships. Experiments show that ICA does improve modeling accuracy and detection performance. Experiments in object detection in cluttered scenes have demonstrated promising results.