This paper describes our contribution to instance search (INS) task for TRECVID 2012. We present four approaches for this task, (i) histograms of SIFT features as feature vectors and Bhatacharya distance for similarity detection (ii) feature vector is combination of SIFT features alone, while for matching we used a basic descriptor matching algorithm (iii) IR based approach using SIFT features ...

In this work, we study efficiency of SIFT descriptor in discrimination of binary shapes. We also analyze how the use of 2 − tuples of SIFT keypoints can affect discrimination of shapes. The study is divided into two parts, the first part serves as a primary analysis where we propose to compute overlap of classes using SIFT and a majority vote of keypoints. In the second part, we analyze both cl...

Semantic Indexing Task (SIN) Run No. Run ID Run Description infMAP (%) 1 F A IUPR-DFKI 1 Fisher Kernel + SVMs 2.86 2 F A IUPR-DFKI 2 Color Correlogram + SVMs 5.38 3 F A IUPR-DFKI 3 Fisher Kernel fused with Color Correlograms + SVMs 5.0 4 F A IUPR-DFKI 4 Fisher Kernel + kNN 0.71 Content-based Copy Detection (CCD) Run No. Run ID Run Description Opt.NDCR 1 *iupr-dfki.fsift F-SIFT+BoW+HE+EWGC 0.776...

Copy-move forgeries are very common image manipulations that are often carried out with malicious intents. Among the techniques devised by the Image Forensic community, those relying on SIFT features are the most effective ones. In this paper we approach the copy-move scenario from the perspective of an attacker whose goal is to remove such features. The attacks conceived so far against SIFT-ba...

Single nucleotide polymorphism (SNP) studies and random mutagenesis projects identify amino acid substitutions in protein-coding regions. Each substitution has the potential to affect protein function. SIFT (Sorting Intolerant From Tolerant) is a program that predicts whether an amino acid substitution affects protein function so that users can prioritize substitutions for further study. We hav...

SIFT is an excellent descriptor to features in medical images. However, the algorithm to achieve SIFT is tedious and takes a long time. To cope with this, we combined image integration and image region partition and proposed a modified SIFT descriptor capable of describing the global energy information of the image. We further proposed a spatial SIFT -oriented non-rigid registration model. Expe...

In this paper, we present local image descriptor using VQ-SIFT for more effective and efficient image retrieval. Instead of SIFT's weighted orientation histograms, we apply vector quantization (VQ) histogram as an alternate representation for SIFT features. Experimental results show that SIFT features using VQ-based local descriptors can achieve better image retrieval accuracy than the conventi...