Albert Hofmann

FACTS - a computer vision system for 3D recovery and semantic mapping of human factors

The study of human attention in the frame of interaction studies has been relevant for usability engineering and ergonomics for decades. Today, with the advent of wearable eye-tracking and Google glasses, monitoring of human attention will soon become ubiquitous. This work describes a multi-component vision system that enables pervasive mapping of human attention. The key contribution is that our methodology enables full 3D recovery of the gaze pointer, human view frustum and associated human centered measurements directly into an automatically computed 3D model. We apply RGB-D SLAM and descriptor matching methodologies for the 3D modeling, localization and fully automated annotation of ROIs (regions of interest) within the acquired 3D model. This methodology brings new potential into automated processing of human factors, opening new avenues for attention studies.

SAM - An Interoperable Metadata Model for Multimodal Surveillance Applications

Metadata interoperability is crucial for various kinds of surveillance applications and systems, e.g. metadata mining in multi-sensor environments, metadata exchange in networked camera systems or information fusion in multi-sensor and multi-detector environments. Different metadata formats have been proposed to foster metadata interoperability, but they show significant limitations. ViPER, CVML and MPEG Visual Surveillance MAF support only the visual modality, CVMLs frame based approach leads to inefficient representation, and MPEG-7s comprehensiveness handicaps its efficient usage for a specific application. To overcome these limitations we propose the Surveillance Application Metadata (SAM) model, capable of describing online and offline analysis results as a set of time lines containing events. A set of sensors, detectors, recorded media items and object instances is described centrally and linked from the event descriptions. The time lines can be related to a subset of sensors and detectors for any modality and different levels of abstraction. Hierarchical classification schemes are used for many purposes, such as types of properties and their values, event types, object classes, coordinate systems etc. in order to allow for application specific adaptations without modifying the data model while ensuring the controlled use of terms. The model supports efficient representation of dense spatio-temporal information such as object trajectories. SAM is not bound to a specific serialization but can be mapped to different existing formats within the limitations evoked by the target format. SAM specifications and examples have been made available

Automated Visual Quality Analysis for Media Production

Automatic quality control for audiovisual media is an important tool in the media production process. In this paper we present tools for assessing the quality of audiovisual content in order to decide about the reusability of archive content. We first discuss automatic detectors for the common impairments noise and grain, video breakups, sharpness, image dynamics and blocking. For the efficient viewing and verification of the automatic results by an operator, three approaches for user interfaces are presented. Finally, we discuss the integration of the tools into a service oriented architecture, focusing on the recent standardization efforts by EBU and AMWAs Joint Task Force on a Framework for Interoperability of Media Services in TV Production (FIMS).

Video analysis tools for annotating user-generated content from social events

In this demo we present how low-level metadata extraction tools have been applied in the context of a pan-European project called Together Anywhere, Together Anytime (TA2). The TA2 project studies new forms of computer-mediated social communications between spatially and temporally distant people. In particular, we concentrate on automatic video analysis tools in an asynchronous community-based video sharing environment called MyVideos, in which users can experience and share personalized music concert videos within their social group.

Tools for semi-automatic monitoring of industrial workflows

This paper describes a tool chain for monitoring complex workflows. Statistics obtained from automatic workflow monitoring in a car assembly environment assist in improving industrial safety and process quality. To this end, we propose automatic detection and tracking of humans and their activity in multiple networked cameras. The described tools offer human operators retrospective analysis of a huge amount of pre-recorded and analyzed footage from multiple cameras in order to get a comprehensive overview of the workflows. Furthermore, the tools help technical administrators in adjusting algorithms by letting the user correct detections (for relevance feedback) and ground truth for evaluation. Another important feature of the tool chain is the capability to inform the employees about potentially risky conditions using the tool for automatic detection of unusual scenes.

A business-driven framework for automatic information extraction in professional media production

Purpose – This paper aims to propose a service-oriented framework for performing content annotation and search, adapted to the task context. Media production workflows are becoming increasingly distributed and heterogeneous.The tasks of professionals in media production can be supported by automatic content analysis and search and retrieval services. Design/methodology/approach – The processes of the framework are derived top-down, starting from business goals and scenarios in audiovisual media production. Formal models of tasks in the production workflow are defined, and business processes are derived from the task models. A software framework enabling the orchestrated execution of these models is developed. Findings – This paper presents a framework that implements the proposed approach called Metadata Production Management Framework (MPMF). The authors show how a media production workflow for a real-world scenario is implemented using the MPMF. Research limitations/implications – The authors have demon...

Improving Preservation and Access Processes of Audiovisual Media by Content-Based Quality Assessment

Quality assessment of audiovisual files is an important tool in many steps of the preservation workflow, as well as for use and access of archive material. Today mainly technical properties of the files can be checked, e.g. file integrity or standards compliance of file wrappers and encoded streams. Checking the audiovisual quality manually results in extremely high labor costs. In this work we present a semi-automatic quality assessment approach that combines the efficiency of fully automatic detection with the interpretation capability of humans to provide verified high quality assessment results. We also address the issue of interoperable metadata for quality assurance, discussing the state of the art and the gaps, and propose a framework for describing visual quality analysis results, which fills one of these gaps.