Behaviours in video

With a significant increment of the number of digital cameras used for various purposes, there is a demanding call for advanced video analysis techniques that can be used to systematically interpret and understand the semantics of video contents, which have been recorded in security surveillance, intelligent transportation, health care, video retrieving and summarization. Understanding and interpreting human behaviours based on video analysis have observed competitive challenges due to non-rigid human motion, self and mutual occlusions, and changes of lighting conditions. To solve these problems, advanced image and signal processing technologies such as neural network, fuzzy logic, probabilistic estimation theory and statistical learning have been overwhelmingly investigated.

A 64-point fourier transform chip for video motion compensation using phase correlation

Details of a new low power fast Fourier transform (FFT) processor for use in digital television applications are presented. This has been fabricated using a 0.6-µm CMOS technology and can perform a 64 point complex forward or inverse FFT on real-time video at up to 18 Megasamples per second. It comprises 0.5 million transistors in a die area of 7.8 × 8 mm and dissipates 1 W. The chip design is based on a novel VLSI architecture which has been derived from a first principles factorization of the discrete Fourier transform (DFT) matrix and tailored to a direct silicon implementation.

Reconfigurable full-search video motion estimation architecture

In this paper, a new reconfigurable multi-standard architecture is introduced for integer-pixel motion estimation and a standard-cell based chip design study is presented. This has been designed to cover most of the common block-based video compression standards, including MPEG-2, MPEG-4, H.263, H.264, AVS and WMV-9. The architecture exhibits simpler control, high throughput and relative low hardware cost and highly competitive when compared with excising designs for specific video standards. It can also, through the use of control signals, be dynamically reconfigured at run-time to accommodate different system constraint such as the trade-off in power dissipation and video-quality. The computational rates achieved make the circuit suitable for high end video processing applications. Silicon design studies indicate that circuits based on this approach incur only a relatively small penalty in terms of power dissipation and silicon area when compared with implementations for specific standards.

Error analysis of FFT architectures for digital video applications

This paper describes how worst-case error analysis can be applied to solve some of the practical issues in the development and implementation of a low power, high performance radix-4 FFT chip for digital video applications. The chip has been fabricated using a 0.6 µm CMOS technology and can perform a 64 point complex forward or inverse FFT on real-time video at up to 18 Megasamples per second. It comprises 0.5 million transistors in a die area of 7.8×8 mm and dissipates 1 W, leading to a cost-effective silicon solution for high quality video processing applications. The analysis focuses on the effect that different radix-4 architectural configurations and finite wordlengths has on the FFT output dynamic range. These issues are addressed using both mathematical error models and through extensive simulation.

The role of imitation in video-based interventions for children with autism.

Objective: The aim of this paper is to bridge the gap between the corpus of imitation research and video-based intervention (VBI) research, and consider the impact imitation skills may be having on VBI outcomes and highlight potential areas for improving efficacy.

Method: A review of the imitation literature was conducted focusing on imitation skill deficits in children with autism followed by a critical review of the video modelling literature focusing on pre-intervention assessment of imitation skills and the impact imitation deficits may have on VBI outcomes.

Results: Children with autism have specific imitation deficits, which may impact VBI outcomes. Imitation training or procedural modifications made to videos may accommodate for these deficits.

Conclusions: There are only six studies where VBI researchers have taken pre-intervention imitation assessments using an assortment of imitation measures. More research is required to develop a standardised multi-dimensional imitation assessment battery that can better inform VBI.

Robust Audio-Visual Speech Recognition under Noisy Audio-Video Conditions

This paper presents the maximum weighted stream posterior (MWSP) model as a robust and efficient stream integration method for audio-visual speech recognition in environments, where the audio or video streams may be subjected to unknown and time-varying corruption. A significant advantage of MWSP is that it does not require any specific measurements of the signal in either stream to calculate appropriate stream weights during recognition, and as such it is modality-independent. This also means that MWSP complements and can be used alongside many of the other approaches that have been proposed in the literature for this problem. For evaluation we used the large XM2VTS database for speaker-independent audio-visual speech recognition. The extensive tests include both clean and corrupted utterances with corruption added in either/both the video and audio streams using a variety of types (e.g., MPEG-4 video compression) and levels of noise. The experiments show that this approach gives excellent performance in comparison to another well-known dynamic stream weighting approach and also compared to any fixed-weighted integration approach in both clean conditions or when noise is added to either stream. Furthermore, our experiments show that the MWSP approach dynamically selects suitable integration weights on a frame-by-frame basis according to the level of noise in the streams and also according to the naturally fluctuating relative reliability of the modalities even in clean conditions. The MWSP approach is shown to maintain robust recognition performance in all tested conditions, while requiring no prior knowledge about the type or level of noise.

Forensic analysis of architectural finishes using fourier transform infrared and raman spectroscopy, part II:White paint

White household paints are commonly encountered as evidence in the forensic laboratory but they often cannot be readily distinguished by color alone so Fourier transform infrared (FT-IR) microscopy is used since it can sometimes discriminate between paints prepared with different organic resins. Here we report the first comparative study of FT-IR and Raman spectroscopy for forensic analysis of white paint. Both techniques allowed the 51 white paint samples in the study to be classified by inspection as either belonging to distinct groups or as unique samples. FT-IR gave five groups and four unique samples; Raman gave seven groups and six unique samples. The basis for this discrimination was the type of resin and/ or inorganic pigments/extenders present. Although this allowed approximately half of the white paints to be distinguished by inspection, the other half were all based on a similar resin and did not contain the distinctive modifiers/pigments and extenders that allowed the other samples to be identified. The experimental uncertainty in the relative band intensities measured using FT-IR was similar to the variation within this large group, so no further discrimination was possible. However, the variation in the Raman spectra was larger than the uncertainty, which allowed the large group to be divided into three subgroups and four distinct spectra, based on relative band intensities. The combination of increased discrimination and higher sample throughput means that the Raman method is superior to FT-IR for samples of this type. © 2005 Society for Applied Spectroscopy.

Real-Time Face Recognition from Surveillance Video

This chapter describes an experimental system for the recognition of human faces from surveillance video. In surveillance applications, the system must be robust to changes in illumination, scale, pose and expression. The system must also be able to perform detection and recognition rapidly in real time. Our system detects faces using the Viola-Jones face detector, then extracts local features to build a shape-based feature vector. The feature vector is constructed from ratios of lengths and differences in tangents of angles, so as to be robust to changes in scale and rotations in-plane and out-of-plane. Consideration was given to improving the performance and accuracy of both the detection and recognition steps.