Partitioning a video sequence into shots is the first step toward video-content analysis and content-based video browsing and retrieval. A video shot is defined as a series of interrelated consecutive frames taken contiguously by a single camera and representing a continuous action in time and space. As such, shots are considered to be the primitives for higher level content analysis, indexing,...

This paper describes the contribution of the TZI to the shot detection task of the TREC 2003 video analysis track (TRECVID). The approach comprises a feature extraction step and a shot detection step. In the feature extraction, three features are extracted: a frequency-domain approach based on FFT-features, a spatial-domain approach based on changes in the image luminance values, and another sp...

A significant barrier to applying the techniques of machine learning to the domain of object boundary detection is the need to obtain a large database of correctly labeled examples. Inspired by developmental psychology, this paper proposes that boundary detection can be learned from the output of a motion tracking algorithm that separates moving objects from their static surroundings. Motion se...

The objective of this work is the detection of object classes, such as airplanes or horses. Instead of using a model based on salient image fragments, we show that object class detection is also possible using only the object’s boundary. To this end, we develop a novel learning technique to extract class-discriminative boundary fragments. In addition to their shape, these “codebook” entries als...

Shot and classification is first and foremost step for further analysis of video content . A Shot is defined as a set of frames from a single camera. Processing of video and image facilitates better understanding of the scene that it describe. It is a fundamental component of a number of technologies like video surveillance, robotics etc .A scene is a collection of one or more shots focusing on...

This paper considers the problem of detecting lines in speckle imagery, such as that produced by synthetic aperture radar (SAR) or ultrasound techniques. Using the physical principles that account for the speckle phenomenon, we derive the optimal detector for lines in fully developed speckle, and we compare the optimal detector to several suboptimal detection rules that are more computationally...

Structure in music is traditionally analyzed hierarchically: large-scale sections can be sub-divided and refined down to the short melodic ideas at the motivic level. However, typical algorithmic approaches to structural annotation produce flat temporal partitions of a track, which are commonly evaluated against a similarly flat, human-produced annotation. Evaluating structure analysis as repre...

In this paper we investigate the automatic detection of phoneme boundaries in audio recordings with the help of deep bidirectional LSTMs. This work is motivated by the needs of the project BULB which aims to support linguists in documenting unwritten languages. The automatic detection of phoneme boundaries in audio recordings of a new language is part of the technical requirements of the BULB p...

In this paper, we present a framework for analyzing video using selfsimilarity. Video scenes are located by analyzing inter-frame similarity matrices. The approach is flexible to the choice of both feature parametrization and similarity measure and it is robust because the data is used to model itself. We present the approach and its application to shot boundary detection.

A scene boundary detection method is presented, which analyzes both aural and visual information sources and accounts for their inter-relations and coincidence to semantically identify video scenes. Audio analysis focuses on the segmentation of the audio source into three types of semantic primitives, i.e. silence, speech and music. Further processing on speech segments aims at locating speaker...