IEEE Trans Pattern Anal Mach Intell - Object Tracking by Oversampling Local Features.

Tópicos

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Resumo

In this paper, we present the ALIEN tracking method that exploits oversampling of local invariant representations to build a robust object/context discriminative classifier. To this end, we use multiple instances of scale invariant local features weakly aligned to the object template. This allows to take account of 3D shape deviations from planarity and their interactions with shadows, occlusions and sensor quantization for which no invariant representations can be defined. A non parametric learning algorithm based on the transitive matching property discriminates the object from the context and prevents improper object template updating during occlusions. We show that our learning rule has asymptotic stability under mild conditions and confirms the drift-free capability of the method in long term tracking. A real-time implementation of the ALIEN tracker has been evaluated in comparison with the state of the art tracking systems on an extensive set of publicly available video sequences that represent most of the critical conditions occurring in real tracking environments. We have reported superior or equal performance in most of the cases and verified tracking with no drifting in very long video sequences.

Resumo Limpo

paper present alien track method exploit oversampl local invari represent build robust objectcontext discrimin classifi end use multipl instanc scale invari local featur weak align object templat allow take account d shape deviat planar interact shadow occlus sensor quantiz invari represent can defin non parametr learn algorithm base transit match properti discrimin object context prevent improp object templat updat occlus show learn rule asymptot stabil mild condit confirm driftfre capabl method long term track realtim implement alien tracker evalu comparison state art track system extens set public avail video sequenc repres critic condit occur real track environ report superior equal perform case verifi track drift long video sequenc

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