Phase-shifting profilometry combined with Gray-code patterns projection has been widely used for 3D measurement. In this technique, a phase-shifting algorithm is used to calculate the wrapped phase, and a set of Gray-code binary patterns is used to determine the unwrapped phase. In the real measurement, the captured Gray-code patterns are no longer binary, resulting in phase unwrapping errors at a large number of erroneous pixels. Although this problem has been attended and well resolved by a few methods, it remains challenging when a measured object has step-heights and the captured patterns contain invalid pixels. To effectively remove unwrapping errors and simultaneously preserve step-heights, in this paper, an effective method using an adaptive median filter is proposed. Both simulations and experiments can demonstrate its effectiveness.

Phase-shifting profilometry combined with Gray-code patterns projection: unwrapping error removal by an adaptive median filter.

https://hal.archives-ouvertes.fr/hal-01724317/document

On the role and the importance of features for background modeling and foreground detection

Moving object detection in the H.264/AVC compressed domain for video surveillance applications

Image and video analysis requires rich features that can characterize various aspects of visual information. These rich features are typically extracted from the pixel values of the images and videos, which require huge amount of computation and seldom useful for real-time analysis. On the contrary, the compressed domain analysis offers relevant information pertaining to the visual content in the form of transform coefficients, motion vectors, quantization steps, coded block patterns with minimal computational burden. The quantum of work done in compressed domain is relatively much less compared to pixel domain. This paper aims to survey various video analysis efforts published during the last decade across the spectrum of video compression standards. In this survey, we have included only the analysis part, excluding the processing aspect of compressed domain. This analysis spans through various computer vision applications such as moving object segmentation, human action recognition, indexing, retrieval, face detection, video classification and object tracking in compressed videos.

A survey on compressed domain video analysis techniques

Robust real-time ship detection and tracking for visual surveillance of cage aquaculture

In order to obtain a useful multichannel publication environment, a content producer has to respect the different terminal and network characteristics of the multimedia devices of its target audience. Embedded scalable video bitstreams, together with a complementary content adaptation framework, give the possibility to respond to heterogeneous usage environments. In this paper, temporally scalable H.264/MPEG-4 AVC encoded bitstreams and bitstreams encoded by relying on the fully-embedded MC-EZBC wavelet-based codec are used. The MPEG-21 Bitstream Syntax Description Language (BSDL) specification is used to generate high-level XML descriptions of the structure of a bitstream. As such, the adaptation of a scalable video stream can be realized in the XML domain, rather than on the bitstream itself. Different transformation technologies are compared to each other as well. Finally, a practical setup of a video streaming use case is discussed by relying on the MPEG-21 BSDL framework.

MPEG-21 bitstream syntax descriptions for scalable video codecs

Background subtraction is a method commonly used to segment objects of interest in image sequences. By comparing new frames to a background model, regions of interest can be found. To cope with highly dynamic and complex environments, a mixture of several models has been proposed in the literature. We propose a novel background subtraction technique derived from the popular mixture of Gaussian models technique (MGM). We discard the Gaussian assumptions and use models existing of an average and an upper and lower threshold. Additionally, we include a maximum difference with the previous value and present an intensity allowance to cope with gradual lighting changes and photon noise, respectively. Moreover, edge-based image segmentation is introduced to improve the results of the proposed technique. This combination of temporal and spatial information results in a robust object detection technique that deals with several difficult situations. Experimental analysis shows that our system is more robust than MGM and more recent techniques, resulting in less false positives and negatives. Finally, a comparison of processing speed shows that our system can process frames up to 50% faster.

Robust spatio-temporal multimodal background subtraction for video surveillance

Personal content management system: A semantic approach

The seamless access to rich multimedia content on any device and over any network, usually known as Universal Multimedia Access, requires interoperable description tools and adaptation techniques to be developed. To address this, MPEG-21 introduces an adaptation framework, which provides several mechanisms for making adaptation decisions according to usage environment and adapting multimedia contents in a coding format independent way. This paper gives an overview of the European FP6 project DANAE which not only implements and extends the existing MPEG-21 adaptation mechanisms but also kicked off several new standardization activities in the area of dynamic and distributed adaptation and resource conversion. MPEG-21 DIP enables static stream selection which is a first step in a series of adaptations. The existing BSD-based adaptation mechanisms enable the efficient implementation of generic adaptation engines, which can be used for existing and future coding formats. These mechanisms were extended to enable dynamic and distributed adaptation. Alternatively to the BSD-based adaptation, resource conversion was investigated which does not rely on scalable media and allows adaptations at the scene level. MPEG-21, Digital Item Adaptation, Resource Conversion, Digital Item Processing, Distributed Adaptation, QoS, QoE, Scalable coding, Efficient use of network/radio

https://biblio.ugent.be/publication/828638/file/828639.pdf

Chris Poppe

Papers

Moving object detection in the H.264/AVC compressed domain for video surveillance applications

MPEG-21 bitstream syntax descriptions for scalable video codecs

Robust spatio-temporal multimodal background subtraction for video surveillance

Personal content management system: A semantic approach

Dynamic and distributed adaptation of scalable multimedia content in a context-aware environment