Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A challenge in 3D computer vision is to automatically acquire 3D models of objects through a CCD camera and to use the acquired models to recognize objects and estimate their poses. The PAMI System works on images acquired from a single CCD camera. It first detects salient features from an image and then groups them according to their types as ll as their spatial, geometrical and topological relations. The feature grouping types include: a) four corner points and triplets of lines forming corners; b) curve segments fitted into ellipses. The use of matching hypotheses generated based on feature groupings is usually more robust and effective than the combinatorial matching of point features.
['Andrew K. C. Wong', 'L. Rong', 'X. Liang']
I am writing a research paper on a idea Robotic vision: 3D object recognition and pose determination
[{"from": "human", "value": "I am writing a research paper on a idea Robotic vision: 3D object recognition and pose determination"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A challenge in 3D computer vision is to automatically acquire 3D models of objects through a CCD camera and to use the acquired models to recognize objects and estimate their poses. The PAMI System works on images acquired from a single CCD camera. It first detects salient features from an image and then groups them according to their types as ll as their spatial, geometrical and topological relations. The feature grouping types include: a) four corner points and triplets of lines forming corners; b) curve segments fitted into ellipses. The use of matching hypotheses generated based on feature groupings is usually more robust and effective than the combinatorial matching of point features."}]