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.

For visual word based location recognition in 3D models we propose a novel distance-weighted scoring scheme. Matching visual words are not treated as perfect matches anymore but are weighted with the distance of the original SIFT feature vectors before quantization. To maintain the scalability and efficiency of vocabulary tree based approaches PCA compressed SIFT feature vectors are used instea...

This paper investigates a face recognition system based on Scale Invariant Feature Transform (SIFT) feature and its distribution on feature space. The system takes advantage of SIFT which possess strong robustness to expression, accessory pose and illumination variations. Since we use each of SIFT keypoint as the feature of face and SIFT keypoints are very complicated in feature space, we apply...

This paper summarizes the three robust feature detection methods: Scale Invariant Feature Transform (SIFT), Principal Component Analysis (PCA)–SIFT and Speeded Up Robust Features (SURF). This paper uses KNN (K-Nearest Neighbor) and Random Sample Consensus (RANSAC) to the three methods in order to analyze the results of the methods’ application in recognition. KNN is used to find the matches, an...

According to SIFT algorithm does not have the property of affine invariance, and the high complexity of time and space, it is difficult to apply to real-time image processing for batch image sequence, so an improved SIFT feature extraction algorithm was proposed in this paper. Firstly, the MSER algorithm detected the maximally stable extremely regions instead of the DOG operator detected extrem...

Scale Invariant Feature Transform (SIFT) has been widely applied, but extracting SIFT feature is complicated and time-consuming. In this paper, to meet the demand of the real-time applications, SIFT is parallelized and optimized on cluster system, which is named pSIFT. Redundancy storage and communication are used for boundary data to improve the performance, and before representation of featur...

..................................................................................................................................... 3 Introduction ................................................................................................................................ 4 Stage (I) ..............................................................................................................