Analysing Animal Behaviour in Wildlife Videos Using Face Detection and Tracking

This paper presents an algorithm that categorises animal locomotive behaviour by combining detection and tracking of animal faces in wildlife videos. As an example, the algorithm is applied to lion faces

Analysis of User Requirements in Interactive 3D Video Systems

The recent development of three dimensional (3D) display technologies has resulted in a proliferation of 3D video production and broadcasting, attracting a lot of research into capture, compression and delivery of stereoscopic content. However, the predominant design practice of interactions with 3D video content has failed to address its differences and possibilities in comparison to the existing 2D video interactions. This paper presents a study of user requirements related to interaction with the stereoscopic 3D video. The study suggests that the change of view, zoom in/out, dynamic video browsing, and textual information are the most relevant interactions with stereoscopic 3D video. In addition, we identified a strong demand for object selection that resulted in a follow-up study of user preferences in 3D selection using virtual-hand and ray-casting metaphors. These results indicate that interaction modality affects users’ decision of object selection in terms of chosen location in 3D, while user attitudes do not have significant impact. Furthermore, the ray-casting-based interaction modality using Wiimote can outperform the volume-based interaction modality using mouse and keyboard for object positioning accuracy

A Survey on Multimodal Video Representation for Semantic Retrieval

This paper surveys the approaches to video representation, focusing on semantic analysis for content-based indexing and retrieval. A problem of adaptive representation of digital multimedia is critically assessed and some novel ideas are presented. Furthermore, the concept of video multimodality is reevaluated and redefined in order to introduce modalities such as editing technique or affect to the audience

An Overview of Multimodal Video Representation for Semantic Analysis

This paper gives an overview of approaches to video representation targeting semantic analysis for content-based indexing and retrieval. It highlights the major achievements of the existing methodologies and sheds new light to the challenges that are still unsolved. The problem of adaptive representation of digital multimedia is critically assessed and some novel ideas are presented. In addition, the concept of video multimodality is reevaluated and redefined in order to introduce the modalities like editing technique. An extensive literature survey on the topics involved is given

A Contextual Study of Semantic Speech Editing in Radio Production

Radio production involves editing speech-based audio using tools that represent sound using simple waveforms. Semantic speech editing systems allow users to edit audio using an automatically generated transcript, which has the potential to improve the production workflow. To investigate this, we developed a semantic audio editor based on a pilot study. Through a contextual qualitative study of five professional radio producers at the BBC, we examined the existing radio production process and evaluated our semantic editor by using it to create programmes that were later broadcast. We observed that the participants in our study wrote detailed notes about their recordings and used annotation to mark which parts they wanted to use. They collaborated closely with the presenter of their programme to structure the contents and write narrative elements. Participants reported that they often work away from the office to avoid distractions, and print transcripts so they can work away from screens. They also emphasised that listening is an important part of production, to ensure high sound quality. We found that semantic speech editing with automated speech recognition can be used to improve the radio production workflow, but that annotation, collaboration, portability and listening were not well supported by current semantic speech editing systems. In this paper, we make recommendations on how future semantic speech editing systems can better support the requirements of radio production

Tracking Animals In Wildlife Videos

This paper presents an algorithm for detection and tracking of animal faces in wildlife videos. As an example the algorithm is applied to lion faces. The detection algorithm is based on a human face detection method, utilising Haar-like features and AdaBoost classifiers. The face tracking is implemented using the Kanade-Lucas-Tomasi tracker and by applying a specific interest model to the detected face. By combining the two methods in a specific tracking model, a reliable and temporally coherent detection/tracking of animal faces is achieved. In addition to the detection of particular animal species, the information generated by the tracker can be used to boost the priors in the probabilistic semantic classification of wildlife video