Unsupervised Human Action Detection by Action Matching

We propose a new task of unsupervised action detection by action matching. Given two long videos, the objective is to temporally detect all pairs of matching video segments. A pair of video segments are matched if they share the same human action. The task is category independent---it does not matter what action is being performed---and no supervision is used to discover such video segments. Unsupervised action detection by action matching allows us to align videos in a meaningful manner. As such, it can be used to discover new action categories or as an action proposal technique within, say, an action detection pipeline. Moreover, it is a useful pre-processing step for generating video highlights, e.g., from sports videos. We present an effective and efficient method for unsupervised action detection. We use an unsupervised temporal encoding method and exploit the temporal consistency in human actions to obtain candidate action segments. We evaluate our method on this challenging task using three activity recognition benchmarks, namely, the MPII Cooking activities dataset, the THUMOS15 action detection benchmark and a new dataset called the IKEA dataset. On the MPII Cooking dataset we detect action segments with a precision of 21.6% and recall of 11.7% over 946 long video pairs and over 5000 ground truth action segments. Similarly, on THUMOS dataset we obtain 18.4% precision and 25.1% recall over 5094 ground truth action segment pairs.Comment: IEEE International Conference on Computer Vision and Pattern Recognition CVPR 2017 Workshop

Joint Extraction of Entities and Relations Based on a Novel Tagging Scheme

Joint extraction of entities and relations is an important task in information extraction. To tackle this problem, we firstly propose a novel tagging scheme that can convert the joint extraction task to a tagging problem. Then, based on our tagging scheme, we study different end-to-end models to extract entities and their relations directly, without identifying entities and relations separately. We conduct experiments on a public dataset produced by distant supervision method and the experimental results show that the tagging based methods are better than most of the existing pipelined and joint learning methods. What's more, the end-to-end model proposed in this paper, achieves the best results on the public dataset

Identification of novel clostridium perfringens type E strains that carry an iota toxin plasmid with a functional enterotoxin gene

Clostridium perfringens enterotoxin (CPE) is a major virulence factor for human gastrointestinal diseases, such as food poisoning and antibiotic associated diarrhea. The CPE-encoding gene (cpe) can be chromosomal or plasmid-borne. Recent development of conventional PCR cpe-genotyping assays makes it possible to identify cpe location (chromosomal or plasmid) in type A isolates. Initial studies for developing cpe genotyping assays indicated that all cpe-positive strains isolated from sickened patients were typable by cpe-genotypes, but surveys of C. perfringens environmental strains or strains from feces of healthy people suggested that this assay might not be useful for some cpe-carrying type A isolates. In the current study, a pulsed-field gel electrophoresis Southern blot assay showed that four cpe-genotype untypable isolates carried their cpe gene on a plasmid of ~65 kb. Complete sequence analysis of the ~65 kb variant cpe-carrying plasmid revealed no intact IS elements and a disrupted cytosine methyltransferase (dcm) gene. More importantly, this plasmid contains a conjugative transfer region, a variant cpe gene and variant iota toxin genes. The toxin genes encoded by this plasmid are expressed based upon the results of RT-PCR assays. The ~65 kb plasmid is closely related to the pCPF4969 cpe plasmid of type A isolates. MLST analyses indicated these isolates belong to a unique cluster of C. perfringens. Overall, these isolates carrying a variant functional cpe gene and iota toxin genes represent unique type E strains. © 2011 Miyamoto et al

PLASMD BEARING A CDNA COPY OF THE GENOME OF BOVINE VIRAL DIARRHEA VIRUS, CHIMERIC DERIVATIVES THEREOF, AND METHOD OF PRODUCING AN INFECTIOUS BOVINE WRAL DARRHEAVIRUS USING SAD PLASMID

A plasmid bearing a cDNA copy of the genome of bovine viral diarrhea virus (BVDV), chimeric derivatives of the plasmid and a method of producing an infectious bovine viral diarrhea virus using the plasmid are disclosed. The invention relates to a plasmid DNA molecule that replicates easily in E. coli and contains a sufficient portion of the genome of BVDV, cloned as cDNA, to be a suitable template to produce RNA in vitro which, upon transfection into bovine cells, gives rise to infectious BVDV. The BVDV created by the process of the invention can be engineered for use as a vector in many advantageous applications

ARCHANGEL: Tamper-proofing Video Archives using Temporal Content Hashes on the Blockchain

We present ARCHANGEL; a novel distributed ledger based system for assuring the long-term integrity of digital video archives. First, we describe a novel deep network architecture for computing compact temporal content hashes (TCHs) from audio-visual streams with durations of minutes or hours. Our TCHs are sensitive to accidental or malicious content modification (tampering) but invariant to the codec used to encode the video. This is necessary due to the curatorial requirement for archives to format shift video over time to ensure future accessibility. Second, we describe how the TCHs (and the models used to derive them) are secured via a proof-of-authority blockchain distributed across multiple independent archives. We report on the efficacy of ARCHANGEL within the context of a trial deployment in which the national government archives of the United Kingdom, Estonia and Norway participated.Comment: Accepted to CVPR Blockchain Workshop 201