Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  focuses on a method of constructing panoramas from a quadcopter, and a new mosaicing sub-problem when the scene contains significant regions of vacant spaces. These vacant spaces yield little to no features to match input images and hence challenge existing mosaicing techniques.  describe a framework that is able to handle this unique input by leveraging the availability of the inertial measurement unit (IMU) data from the quadcopter. Specifically, our method uses the imprecise IMU data accompanying a video to select a subset of images that contain interesting scene content. When the scene is such that this subset contains no vacant space, an appropriate panorama is effected; hover, with featureless spaces, existing mo-saicing methods do not work. , the subset is partitioned into multiple clusters. These subsets can now be stitched into a series of mini-panoramas, but a complete mosaic is not yet available. The gaps beten these minipanoramas represent regions of featureless spaces in the scene. Therefore,  once again use the IMU data together with a novel stereo reconstruction to determine appropriate portions of the images to complete the panorama.  demonstrate the efficacy of our approach on a number of input sequences that cannot be mosaiced by existing methods.
['Meghshyam G. Prasad', 'Sharat Chandran', 'Michael S. Brown']
I am writing a research paper on a idea Mosaicing scenes with a quadcopter
[{"from": "human", "value": "I am writing a research paper on a idea Mosaicing scenes with a quadcopter"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  focuses on a method of constructing panoramas from a quadcopter, and a new mosaicing sub-problem when the scene contains significant regions of vacant spaces. These vacant spaces yield little to no features to match input images and hence challenge existing mosaicing techniques.  describe a framework that is able to handle this unique input by leveraging the availability of the inertial measurement unit (IMU) data from the quadcopter. Specifically, our method uses the imprecise IMU data accompanying a video to select a subset of images that contain interesting scene content. When the scene is such that this subset contains no vacant space, an appropriate panorama is effected; hover, with featureless spaces, existing mo-saicing methods do not work. , the subset is partitioned into multiple clusters. These subsets can now be stitched into a series of mini-panoramas, but a complete mosaic is not yet available. The gaps beten these minipanoramas represent regions of featureless spaces in the scene. Therefore,  once again use the IMU data together with a novel stereo reconstruction to determine appropriate portions of the images to complete the panorama.  demonstrate the efficacy of our approach on a number of input sequences that cannot be mosaiced by existing methods."}]