A novel adaptive video object tracking algorithm is proposed using intensity based and feature based techniques which results in improved reliability and at the same time it aims to reduce computational complexity. This is achieved by intelligently combining SIFT and BMA and making it adaptive to the speed of the moving object. Tracking frame by frame using SIFT which is successful for detectin...

Success of scale-invariant feature transform (SIFT) image registration is limited when attempted on camera footage taken under water. This is, largely due to the poor image quality inherent to imaging in aquatic environments. In this research we aim to overcome this shortcoming using a new method of pre-processing of true-color imagery taken under water based on the Contrast Limited Adaptive Hi...

Materials genome initiatives sift big data.

Over the last decade, there have been renewed efforts into wine grape breeding within research community. Quick characterisation by phenotyping of quality traits, including aroma composition, remains challenging. Selected Ion Flow Tube Mass Spectrometry (SIFT-MS), a high throughput soft ionisation technology first available in 2008, could be particularly useful for this purpose. In light this, ...

Scale Invariant Feature Transform (SIFT) is a method for extracting distinctive invariant feature from images [1]. SIFT has been applied to many problems such as face recognition and object recognition [18], [19], [20], [21]. We have analyzed performance of SIFT using Euclidean distance as a matching algorithm. Further the matching rate can be enhanced/improved by changing distance calculation ...