This paper describes the motivations, methods, and automation architecture of a framework for multisource Semantic Information extraction & Fusion for collaborative Threat assessment (SIFT). First, the technical and pragmatic challenges that motivate the research ideas are summarized. Next, a characterization of the activities for generating decision enabling information from multi-source data ...

This paper presents a comparative approach for Content Based Image Retrieval (CBIR) using Scale Invariant Feature Transform (SIFT) algorithm and Principal Component Analysis (PCA) for color images. The motivation to use SIFT algorithm for CBIR is due to the fact that SIFT is invariant to scale, rotation and translation as well as partially invariant to affine distortion and illumination changes...

With explosive growth of multimedia data on internet, the effective information retrieval from a large scale of multimedia data becomes more and more important. To retrieve these multimedia data automatically, some features in them must be extracted. Hence, image feature extraction algorithms have been a fundamental component of multimedia retrieval. Among these algorithms, Scale Invariant Feat...

The traditional scale invariant feature transform (SIFT) method can extract distinctive features for image matching. However, it is extremely time-consuming in SIFT matching because of the use of the Euclidean distance measure. Recently, many binary SIFT (BSIFT) methods have been developed to improve matching efficiency; however, none of them is invariant to mirror reflection. To address these ...

As multimedia data sharing increases, security in mobile devices and its mechanism can be seen as critical. Biometrics combines the physiological behavioral qualities of an individual to validate their character real-time. Humans incorporate attributes like a fingerprint, face, iris, palm print, finger knuckle Deoxyribonucleic Acid (DNA), walk, voice, mark, or keystroke. The main goal this pape...

In this paper we describe our experiments in the automatic search task of TRECVid 2007. For this we have implemented a new video search technique based on SIFT features and manual annotation. We submitted two runs, one solely based on the SIFT features with keyframe matching and the other based on adapted SIFT features for video retrieval in addition to manually annotated data.