Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Local features are widely used in visual tracking to improve robustness in cases of partial occlusion, deformation and rotation.  proposes a local fragment-based object tracking algorithm. Unlike many existing fragment-based algorithms that allocate the ights to each fragment, this method firstly defines discrimination and uniqueness for local fragment, and builds an automatic pre-selection of useful fragments for tracking. Then, a Harris-SIFT filter is used to choose the current valid fragments, excluding occluded or highly deformed fragments. Based on those valid fragments, fragment-based color histogram provides a structured and effective description for the object. Finally, the object is tracked using a valid fragment template combining the displacement constraint and similarity of each valid fragment. The object template is updated by fusing feature similarity and valid fragments, which is scale-adaptive and robust to partial occlusion. The experimental results show that the proposed algorithm is accurate and robust in challenging scenarios.
['Jin Zheng', 'Bo Li', 'Peng Tian', 'Gang Luo']
I am writing a research paper on a idea Robust Object Tracking Using Valid Fragments Selection
[{"from": "human", "value": "I am writing a research paper on a idea Robust Object Tracking Using Valid Fragments Selection"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Local features are widely used in visual tracking to improve robustness in cases of partial occlusion, deformation and rotation.  proposes a local fragment-based object tracking algorithm. Unlike many existing fragment-based algorithms that allocate the ights to each fragment, this method firstly defines discrimination and uniqueness for local fragment, and builds an automatic pre-selection of useful fragments for tracking. Then, a Harris-SIFT filter is used to choose the current valid fragments, excluding occluded or highly deformed fragments. Based on those valid fragments, fragment-based color histogram provides a structured and effective description for the object. Finally, the object is tracked using a valid fragment template combining the displacement constraint and similarity of each valid fragment. The object template is updated by fusing feature similarity and valid fragments, which is scale-adaptive and robust to partial occlusion. The experimental results show that the proposed algorithm is accurate and robust in challenging scenarios."}]