Detection of setting and subject information in documentary video

Interpretation of video information is a difficult task for computer vision and machine intelligence. In this paper we examine the utility of a non-image based source of information about video contents, namely the shot list, and study its use in aiding image interpretation. We show how the shot list may be analysed to produce a simple summary of the \u27who and where\u27 of a documentary or interview video. In order to detect the subject of a video we use the notion of a \u27shot syntax\u27 of a particular genre to isolate actual interview sections

Two-dimensional string notation for representing video sequences

Most current work on video indexing concentrates on queries which operate over high level semantic information which must be entirely composed and entered manually. We propose an indexing system which is based on spatial information about key objects in a scene. These key objects may be detected automatically, with manual supervision, and tracked through a sequence using one of a number of recently developed techniques. This representation is highly compact and allows rapid resolution of queries specified by iconic example. A number of systems have been produced which use 2D string notations to index digital image libraries. Just as 2D strings provide a compact and tractable indexing notation for digital pictures, a sequence of 2D strings might provide an index for a video or image sequence. To improve further upon this we reduce the representation to the 2D string pair representing the initial frame, and a sequence of edits to these strings. This takes advantage of the continuity between frames to further reduce the size of the notation. By representing video sequences using string edits, a notation has been developed which is compact, and allows querying on the spatial relationships of objects to be performed without rebuilding the majority of the scene. Calculating ranks of objects directly from the edit sequence allows matching with minimal calculation, thus greatly reducing search time. This paper presents the edit sequence notation and algorithms for evaluating queries over image sequences. A number of optimizations which represent a considerably saving in search time is demonstrated in the paper

An efficient least common subgraph algorithm for video indexing

Many tasks in computer vision can be expressed as graph problems. This allows the task to be solved using a well studied algorithm, however many of these algorithms are of exponential complexity. This is a disadvantage when considered in the context of searching a database of images or videos for similarity. Work by Mesaner and Bunke (1995) has suggested a new class of graph matching algorithms which uses a priori knowledge about a database of models to reduce the time taken during online classification. This paper presents a new algorithm which extends the earlier work to detection of the largest common subgraph.<br /

Massively parallel rare disease genetics

A report on the 'Genomic Disorders 2011 - The Genomics of Rare Diseases' meeting, Wellcome Trust Sanger Institute, Hinxton, UK, 23-26 March 201

Hypothermia, immune suppression and SDD: can we have our cake and eat it?

In vitro studies and clinical observations suggest that both accidental and controlled/therapeutic hypothermia have a strong immunosuppressive effect, and that hypothermia increases the risk of infections, especially wound infections and pneumonia. In the previous issue of Critical Care, Kamps and colleagues report that when hypothermia was used for prolonged periods in patients with severe traumatic brain injury in conjunction with selective decontamination of the digestive tract, the risks of infection were the same or lower in patients treated with therapeutic cooling. The risk of infection is widely regarded as the most important danger of therapeutic cooling. The findings of Kamps and colleagues need to be verified in prospective trials and in higher-resistance environments, but raise the possibility of cooling for prolonged periods with greatly reduced risk. We may be able to have our cake and eat it

Artifacts of the colour coherence vector and an alternative similarity measure

Image similarity measures can be used to capture useful structure in video processing. In this paper one popular variation, the colour coherence vector, is discussed. It is shown to perform poorly for certain tasks and a simpler, but more effective alternative is proposed. This alternative is examined for the initial task of anchor person spotting in news broadcasts, and extended to generic interview detection

ASYMMETRIC FILTER FOR TEXT RECOGNITION IN VIDEO

Stripes are a common sub-structure of text characters, and the scale of the stripes does not vary significantly within a character. In this paper a new form of filter is derived from the Gabor filter which can efficiently estimate the scales of such stripes. The contrast of text in video can then be increased by enhancing the edges of those stripes found to have a suitable scale. The algorithm presented enhances the stripes in three selected scale ranges. Character recognition is then performed on the output of binarizing these enhanced images, and shows improvement over other methods

Text Enhancement with Asymmetric Filter for Video OCR

Stripes are common sub-structures of text characters, and the scale of these stripes varies little within a word. This scale consistency thus provides us with a useful feature for text detection and segmentation. In this paper a new form of filter is derived from the Gabor filter, and it is shown this filter can efficiently estimate the scales of these stripes. The contrast of text in video can then be increased by enhancing the edges of only those stripes found to correspond to a suitable scale. More specifically the algorithm presented here enhances the stripes in three pre-selected scale ranges. The resulting enhancement yields much better performance from the binarization process, which is the step required before character recognition

Incorporating Domain Knowledge with Video and Voice Data Analysis in News Broadcasts

This paper addresses the area of video annotation, indexing and retrieval, and shows how a set of tools can be employed, along with domain knowledge, to detect narrative structure in broadcast news. The initial structure is detected using low-level audio visual processing in conjunction with domain knowledge. Higher level processing may then utilize the initial structure detected to direct processing to improve and extend the initial classification

Text Enhancement with Asymmetric Filter for Video OCR

Stripes are common sub-structures of text characters, and the scale of these stripes varies little within a word. This scale consistency thus provides us with a useful feature for text detection and segmentation. In this paper a new form of filter is derived from the Gabor filter, and it is shown this filter can efficiently estimate the scales of these stripes. The contrast of text in video can then be increased by enhancing the edges of only those stripes found to correspond to a suitable scale. More specifically the algorithm presented here enhances the stripes in three pre-selected scale ranges. The resulting enhancement yields much better performance from the binarization process, which is the step required before character recognition