183 resultados para video sequence matching


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We present an algorithm for tracking objects in a video sequence, based on a novel approach for motion detection. We do not estimate the velocity �eld. In-stead we detect only the direction of motion at edge points and thus isolate sets of points which are moving coherently. We use a Hausdor� distance based matching algorithm to match point sets in local neighborhood and thus track objects in a video sequence. We show through some examples the e�ectiveness of the algo- rithm.

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This paper discusses a novel high-speed approach for human action recognition in H. 264/AVC compressed domain. The proposed algorithm utilizes cues from quantization parameters and motion vectors extracted from the compressed video sequence for feature extraction and further classification using Support Vector Machines (SVM). The ultimate goal of our work is to portray a much faster algorithm than pixel domain counterparts, with comparable accuracy, utilizing only the sparse information from compressed video. Partial decoding rules out the complexity of full decoding, and minimizes computational load and memory usage, which can effect in reduced hardware utilization and fast recognition results. The proposed approach can handle illumination changes, scale, and appearance variations, and is robust in outdoor as well as indoor testing scenarios. We have tested our method on two benchmark action datasets and achieved more than 85% accuracy. The proposed algorithm classifies actions with speed (>2000 fps) approximately 100 times more than existing state-of-the-art pixel-domain algorithms.

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H. 264/advanced video coding surveillance video encoders use the Skip mode specified by the standard to reduce bandwidth. They also use multiple frames as reference for motion-compensated prediction. In this paper, we propose two techniques to reduce the bandwidth and computational cost of static camera surveillance video encoders without affecting detection and recognition performance. A spatial sampler is proposed to sample pixels that are segmented using a Gaussian mixture model. Modified weight updates are derived for the parameters of the mixture model to reduce floating point computations. A storage pattern of the parameters in memory is also modified to improve cache performance. Skip selection is performed using the segmentation results of the sampled pixels. The second contribution is a low computational cost algorithm to choose the reference frames. The proposed reference frame selection algorithm reduces the cost of coding uncovered background regions. We also study the number of reference frames required to achieve good coding efficiency. Distortion over foreground pixels is measured to quantify the performance of the proposed techniques. Experimental results show bit rate savings of up to 94.5% over methods proposed in literature on video surveillance data sets. The proposed techniques also provide up to 74.5% reduction in compression complexity without increasing the distortion over the foreground regions in the video sequence.

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This paper discusses a novel high-speed approach for human action recognition in H.264/AVC compressed domain. The proposed algorithm utilizes cues from quantization parameters and motion vectors extracted from the compressed video sequence for feature extraction and further classification using Support Vector Machines (SVM). The ultimate goal of the proposed work is to portray a much faster algorithm than pixel domain counterparts, with comparable accuracy, utilizing only the sparse information from compressed video. Partial decoding rules out the complexity of full decoding, and minimizes computational load and memory usage, which can result in reduced hardware utilization and faster recognition results. The proposed approach can handle illumination changes, scale, and appearance variations, and is robust to outdoor as well as indoor testing scenarios. We have evaluated the performance of the proposed method on two benchmark action datasets and achieved more than 85 % accuracy. The proposed algorithm classifies actions with speed (> 2,000 fps) approximately 100 times faster than existing state-of-the-art pixel-domain algorithms.

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Moving shadow detection and removal from the extracted foreground regions of video frames, aim to limit the risk of misconsideration of moving shadows as a part of moving objects. This operation thus enhances the rate of accuracy in detection and classification of moving objects. With a similar reasoning, the present paper proposes an efficient method for the discrimination of moving object and moving shadow regions in a video sequence, with no human intervention. Also, it requires less computational burden and works effectively under dynamic traffic road conditions on highways (with and without marking lines), street ways (with and without marking lines). Further, we have used scale-invariant feature transform-based features for the classification of moving vehicles (with and without shadow regions), which enhances the effectiveness of the proposed method. The potentiality of the method is tested with various data sets collected from different road traffic scenarios, and its superiority is compared with the existing methods. (C) 2013 Elsevier GmbH. All rights reserved.

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In this work, we have explored the prospect of segmenting crowd flow in H. 264 compressed videos by merely using motion vectors. The motion vectors are extracted by partially decoding the corresponding video sequence in the H. 264 compressed domain. The region of interest ie., crowd flow region is extracted and the motion vectors that spans the region of interest is preprocessed and a collective representation of the motion vectors for the entire video is obtained. The obtained motion vectors for the corresponding video is then clustered by using EM algorithm. Finally, the clusters which converges to a single flow are merged together based on the bhattacharya distance measure between the histogram of the of the orientation of the motion vectors at the boundaries of the clusters. We had implemented our proposed approach on the complex crowd flow dataset provided by 1] and compared our results by using Jaccard measure. Since we are performing crowd flow segmentation in the compressed domain using only motion vectors, our proposed approach performs much faster compared to other pixel domain counterparts still retaining better accuracy.

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We present a new method for establishing correlation between deuterium and its attached carbon in a deuterated liquid crystal. The method is based on transfer of polarization using the DAPT pulse sequence proposed originally for two spin half nuclei, now extended to a spin-1 and a spin-1/2 nuclei. DAPT utilizes the evolution of magnetization of the spin pair under two blocks of phase shifted BLEW-12 pulses on one of the spins separated by a 90 degree pulse on the other spin. The method is easy to implement and does not need to satisfy matching conditions unlike the Hartmann-Hahn cross-polarization. Experimental results presented demonstrate the efficacy of the method.

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Scalable video coding (SVC) is an emerging standard built on the success of advanced video coding standard (H.264/AVC) by the Joint video team (JVT). Motion compensated temporal filtering (MCTF) and Closed loop hierarchical B pictures (CHBP) are two important coding methods proposed during initial stages of standardization. Either of the coding methods, MCTF/CHBP performs better depending upon noise content and characteristics of the sequence. This work identifies other characteristics of the sequences for which performance of MCTF is superior to that of CHBP and presents a method to adaptively select either of MCTF and CHBP coding methods at the GOP level. This method, referred as "Adaptive Decomposition" is shown to provide better R-D performance than of that by using MCTF or CRBP only. Further this method is extended to non-scalable coders.

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We have identified strong topoisomerase sites (STS) for Mycobacteruim smegmatis topoisomerase I in double-stranded DNA context using electrophoretic mobility shift assay of enzyme-DNA covalent complexes; Mg2+, an essential component for DNA relaxation activity of the enzyme, is not required for binding to DNA, The enzyme makes single-stranded nicks, with transient covalent interaction at the 5'-end of the broken DNA strand, a characteristic akin to prokaryotic topoisomerases. More importantly, the enzyme binds to duplex DNA having a preferred site with high affinity, a. property similar to the eukaryotic type I topoisomerases, The preferred cleavage site is mapped on a 65 bp duplex DNA and found to be CG/TCTT. Thus, the enzyme resembles other prokaryotic type I topoisomerases in mechanistics of the reaction, but is similar to eukaryotic enzymes in DNA recognition properties.

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Treatment of bromoketals 2, derived from allyl alcohols 1, with tributyltin chloride, sodium cyanoborohydride and AIBN furnishes the tetrahydrofurannulated products 3 via a 5-exo-trig radical cyclisation reaction followed by reductive cleavage of ketal 4.

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Jacalin and artocarpin, the two lectins from jackfruit (Artocarpus integrifolia) seeds, have different physicochemical properties and carbohydrate-binding specificities. However, comparison of the partial amino-acid sequence of artocarpin with the known sequence of jacalin indicates close to 50% sequence identity. Artocarpin crystallizes in two forms, both monoclinic P2(1), with one and two tetramic molecules, respectively, in the asymmetric units of form I (a = 69.9, b = 73.7, c = 60.6 Angstrom and beta = 95.1 degrees) and form II (a = 87.6, b = 72.2, c = 92.6 Angstrom and beta = 101.1 degrees). Both the crystal structures have been solved by the molecular replacement method using the known structure of jacalin as the search model and ope of them partially refined, confirming that the two lectins are indeed homologous.

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With the availability of a huge amount of video data on various sources, efficient video retrieval tools are increasingly in demand. Video being a multi-modal data, the perceptions of ``relevance'' between the user provided query video (in case of Query-By-Example type of video search) and retrieved video clips are subjective in nature. We present an efficient video retrieval method that takes user's feedback on the relevance of retrieved videos and iteratively reformulates the input query feature vectors (QFV) for improved video retrieval. The QFV reformulation is done by a simple, but powerful feature weight optimization method based on Simultaneous Perturbation Stochastic Approximation (SPSA) technique. A video retrieval system with video indexing, searching and relevance feedback (RF) phases is built for demonstrating the performance of the proposed method. The query and database videos are indexed using the conventional video features like color, texture, etc. However, we use the comprehensive and novel methods of feature representations, and a spatio-temporal distance measure to retrieve the top M videos that are similar to the query. In feedback phase, the user activated iterative on the previously retrieved videos is used to reformulate the QFV weights (measure of importance) that reflect the user's preference, automatically. It is our observation that a few iterations of such feedback are generally sufficient for retrieving the desired video clips. The novel application of SPSA based RF for user-oriented feature weights optimization makes the proposed method to be distinct from the existing ones. The experimental results show that the proposed RF based video retrieval exhibit good performance.

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Elucidation of the detailed structural features and sequence requirements for iv helices of various lengths could be very important in understanding secondary structure formation in proteins and, hence. in the protein folding mechanism. An algorithm to characterize the geometry of an alpha helix from its C-alpha coordinates has been developed and used to analyze the structures of long cu helices (number of residues greater than or equal to 25) found in globular proteins, the crystal structure coordinates of which are available from the Brookhaven Protein Data Bank, Ail long a helices can be unambiguously characterized as belonging to one of three classes: linear, curved, or kinked, with a majority being curved. Analysis of the sequences of these helices reveals that the long alpha helices have unique sequence characteristics that distinguish them from the short alpha helices in globular proteins, The distribution and statistical propensities of individual amino acids to occur in long alpha heices are different from those found in short alpha helices, with amino acids having longer side chains and/or having a greater number of functional groups occurring more frequently in these helices, The sequences of the long alpha helices can be correlated with their gross structural features, i.e., whether they are curved, linear, or kinked, and in case of the curved helices, with their curvature.

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The genomic sequences of several RNA plant viruses including cucumber mosaic virus, brome mosaic virus, alfalfa mosaic virus and tobacco mosaic virus have become available recently. The former two viruses are icosahedral while the latter two are bullet and rod shaped, respectively in particle morphology. The non-structural 3a proteins of cucumber mosaic virus and brome mosaic virus have an amino acid sequence homology of 35% and hence are evolutionarily related. In contrast, the coat proteins exhibit little homology, although the circular dichroism spectrum of these viruses are similar. The non-coding regions of the genome also exhibit variable but extensive homology. Comparison of the brome mosaic virus and alfalfa mosaic virus sequences reveals that they are probably related although with a much larger evolutionary distance. The polypeptide folds of the coat protein of three biologically distinct isometric plant viruses, tomato bushy stunt virus, southern bean mosaic virus and satellite tobacco necrosis virus have been shown to display a striking resemblance. All of them consist of a topologically similar 8-standard β-barrel. The implications of these studies to the understanding of the evolution of plant viruses will be discussed.

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Amino acid sequences are known to constantly mutate and diverge unless there is a limiting condition that makes such a change deleterious. However, closer examination of the sequence and structure reveals that a few large, cryptic repeats are nevertheless sequentially conserved. This leads to the question of why only certain repeats are conserved at the sequence level. It would be interesting to find out if these sequences maintain their conservation at the three-dimensional structure level. They can play an active role in protein and nucleotide stability, thus not only ensring proper functioning but also potentiating malfunction and disease. Therefore, insights into any aspect of the repeats - be it structure, function or evolution - would prove to be of some importance. This study aims to address the relationship between protein sequence and its three-dimensional structure, by examining if large cryptic sequence repeats have the same structure.