Finding the optimal temporal partitioning of video sequences

The existing techniques for shot partitioning either process each shot boundary independently or proceed sequentially. The sequential process assumes the last shot boundary is correctly detected and utilizes the shot length distribution to adapt the threshold for detecting the next boundary. These techniques are only locally optimal and suffer from the strong assumption about the correct detection of the last boundary. Addressing these fundamental issues, in this paper, we aim to find the global optimal shot partitioning by utilizing Bayesian principles to model the probability of a particular video partition being the shot partition. A computationally efficient algorithm based on Dynamic Programming is then formulated. The experimental results on a large movie set show that our algorithm performs consistently better than the best adaptive-thresholding technique commonly used for the task.

Explicit state duration HMM for abnormality detection in sequences of human activity

The importance of explicit duration modelling for classification of sequences of human activity and the reliable and timely detection of duration abnormality was highlighted. The normal classes of behavior were designed to highlight the importance of modelling duration given the limitations of the tracking system. It was found that HMM was the weakest model for classification of the unseen normal sequences with 81% accuracy. Long term abnormality was investigated by artificially varying the duration of primary activity in a randomly selected test sequence. The incorporation of duration in models of human behavior is an important consideration for systems seeking to provide cognitive support and to detect deviation in the behavorial patterns.

Media independent knowledge indexing and retrieval

Composing a multimedia presentation may require creation or generation of suitable images and video segments, as well as animation, sound, or special effects. Obtaining images or video sequences can be prohibitively expensive when costs of travel to location, equipment, staff, etc, are considered. Those problems can be alleviated with the use of pictorial and video digital libraries, such libraries require methods for comprehensive indexing and annotation of stored items and efficient retrieval tools.

We propose a system based on user oriented perceptions as they influence query formation in image and video retrieval. We present a method based on user dependent conceptual structures for creating and maintaining indexes to images and video sequences.

Towards detecting patterns of human behaviour from image sequences

This paper details research that will explore the analysis of human behaviour via video surveillance. Digital computer images will be obtained from video footage of a real world scene, and positions of people in the scene will be identified and tracked through each frame in the sequence.

The noted positions will build into a pattern of motion that can be examined and classified. It is proposed that specific events, such as panic or fight situations, will have unique, and therefore identifying, characteristics that will enable automatic detection of such events.

It is envisaged that active cameras will be used when a situation of interest occurs, to enable more information to be extracted from the scene (e.g., panning to follow action, or zooming to enhance detail.)

Mining condensed sets of frequent episodes with more accurate frequencies from complex sequences

Many previous approaches to frequent episode discovery only accept simple sequences. Although a recent approach has been able to nd frequent episodes from complex sequences, the discovered sets are neither condensed nor accurate. This paper investigates the discovery of condensed sets of frequent episodes from complex sequences. We adopt a novel anti-monotonic frequency measure based on non-redundant occurrences, and dene a condensed set, nDaCF (the set of non-derivable approximately closed frequent episodes) within a given maximal error bound of support. We then introduce a series of effective pruning strategies, and develop a method, nDaCF-Miner, for discovering nDaCF sets. Experimental results show that, when the error bound is somewhat high, the discovered nDaCF sets are two orders of magnitude smaller than complete sets, and nDaCF-miner is more efficient than previous mining approaches. In addition, the nDaCF sets are more accurate than the sets found by previous approaches.

Effects of alterations of primer-binding site sequences on human immunodeficiency virus type 1 replication

The human immunodeficiency virus type 1 genomic RNA primer-binding site (PBS) sequence comprises 18 nucleotides which are complementary to those at the 3' end of the replication initiation primer tRNA(3Lys). To investigate the role of the PBS in viral replication, we either deleted the original wild-type PBS (complementary to tRNA(3Lys) or replaced it with DNA sequences complementary to either tRNA(1,2Lys) or tRNA(Phe). Transfection of COS cells with such molecular constructs yielded similar levels of viral progeny that were indistinguishable with regard to viral proteins and tRNA content. Virus particles derived from PBS-deleted molecular clones were noninfectious for MT-4, Jurkat, and CEM-T4 cells. However, infectious viruses were derived from constructs in which the PBS had been altered to sequences complementary to either tRNA(1,2Lys) or tRNA(Phe), although mutated forms showed significant lags in replication efficiency in comparison with wild types. Molecular analysis of reverse-transcribed DNA in cells infected by the mutated viruses indicated that both tRNA(1,2Lys) and tRNA(Phe) could function as primers for reverse transcription during the early stages of infection. Sequencing of full-length proviral DNA, obtained 6 days after infection, revealed the mutated PBS, indicating that a complete cycle of reverse transcription had occurred. During subsequent rounds of infection, reversion of the mutated PBS to wild-type sequences was observed, accompanied by increased production of viral gene products. Reversion to wild-type PBS sequences was confirmed both by specific PCR analysis, using distinct primer pairs, and by direct sequencing of amplified segments. We also performed endogenous in vitro reverse transcription experiments in which synthesis of minus-strand strong-stop viral DNA was primed from a synthetic RNA template containing a PBS complementary to various tRNA isoacceptors. These results showed that tRNA(3Lys) was a much more efficient primer of such reactions than either tRNA(1,2Lys) or tRNA(Phe).

The A-rich RNA sequences of HIV-1 pol are important for the synthesis of viral cDNA

The bias of A-rich codons in HIV-1 pol is thought to be a record of hypermutations in viral genomes that lack biological functions. Bioinformatic analysis predicted that A-rich sequences are generally associated with minimal local RNA structures. Using codon modifications to reduce the amount of A-rich sequences within HIV-1 genomes, we have reduced the flexibility of RNA sequences in pol to analyze the functional significance of these A-rich ‘structurally poor’ RNA elements in HIV-1 pol. Our data showed that codon modification of HIV-1 sequences led to a suppression of virus infectivity by 5–100-fold, and this defect does not correlate with, viral entry, viral protein expression levels, viral protein profiles or virion packaging of genomic RNA. Codon modification of HIV-1 pol correlated with an enhanced dimer stability of the viral RNA genome, which was associated with a reduction of viral cDNA synthesis both during HIV-1 infection and in a cell free reverse transcription assay. Our data provided direct evidence that the HIV-1 A-rich pol sequence is not merely an evolutionary artifact of enzyme-induced hypermutations, and that HIV-1 has adapted to rely on A-rich RNA sequences to support the synthesis of viral cDNA during reverse transcription, highlighting the utility of using ‘structurally poor’ RNA domains in regulating biological process.

Does behavior reflect phylogeny in swiftlets (Aves: Apodidae)? A test using cytochrome b mitochondrial DNA sequences

Swiftlets are small insectivorous birds, many of which nest in caves and are known to echolocate. Due to a lack of distinguishing morphological characters, the taxonomy of swiftlets is primarily based on the presence or absence of echolocating ability, together with nest characters. To test the reliability of these behavioral characters, we constructed an independent phylogeny using cytochrome b mitochondrial DNA sequences from swiftlets and their relatives. This phylogeny is broadly consistent with the higher classification of swifts but does not support the monophyly of swiftlets. Echolocating swiftlets (Aerodramus) and the nonecholocating "giant swiftlet" (Hydrochous gigas) group together, but the remaining nonecholocating swiftlets belonging to Collocalia are not sister taxa to these swiftlets. While echolocation may be a synapomorphy of Aerodramus (perhaps secondarily lost in Hydrochous), no character of Aerodramus nests showed a statistically significant fit to the molecular phylogeny, indicating that nest characters are not phylogenetically reliable in this group.

A framework for identifying affinity classes of inorganic materials binding peptide sequences

With the rapid development of bionanotechnology, there has been a growing interest recently in identifying the affinity classes of the inorganic materials binding peptide sequences. However, there are some distinct characteristics of inorganic materials binding sequence data that limit the performance of many widely-used classification methods. In this paper, we propose a novel framework to predict the affinity classes of peptide sequences with respect to an associated inorganic material. We first generate a large set of simulated peptide sequences based on our new amino acid transition matrix, and then the probability of test sequences belonging to a specific affinity class is calculated through solving an objective function. In addition, the objective function is solved through iterative propagation of probability estimates among sequences and sequence clusters. Experimental results on a real inorganic material binding sequence dataset show that the proposed framework is highly effective on identifying the affinity classes of inorganic material binding sequences.