Monster factory : International dynamics of the Australian horror movie industry

From the early-to-mid 2000s, the Australian horror film production sector has achieved growth and prosperity of a kind not seen since its heyday of the 1980s. Australian horror films can be traced back to the early 1970s, when they experienced a measure of commercial success. However, throughout the twenty-first-century Australian horror gained levels of international recognition that have surpassed the cult status enjoyed by some of the films in the 1970s and 1980s. In recent years, Australia has emerged as a significant producer of breakout, cult, and solid B-grade horror films, which have circulated in markets worldwide. Australian horror’s recent successes have been driven by one of its distinguishing features: its international dimensions. As this chapter argues, the Australian horror film production sector is an export-oriented industry that relies heavily on international partnerships and presales (the sale of distribution rights prior to a film’s completion), and on its relationships with overseas distributors. Yet, these traits vary from film to film as the sector is comprised of several distinct domains of production activity, from guerrilla films destined for niche video markets like specialist cult video stores and online mail-order websites to high(er)-end pictures made for theatrical markets. Furthermore, the content and style of Australian horror movies has often been tailored for export. While some horror filmmakers have sought to play up the Australianness of their product, others have attempted to pass off their films as faux-American or as placeless films effaced of national reference points.

The micro-movie wave in a globalising China : adaptation, formalisation and commercialisation

While user-generated short online videos have existed since the emergence of video sharing sites in China, they have undergone a process of formalisation and commercialisation, culminating in the wave of micro-movies in recent years. By addressing the wider context of globalisation alongside relevant state policies and shifting viewing habits, this article analyses the local and global causes of this wave. It offers evidence that illustrates how online video service providers in China have adapted in a changing industry landscape as they negotiate state policies, advertiser interests and user preference. It then examines the production and distribution dynamics, where professional producers draw on social media, grassroots creativity and creative talents in regional markets. Finally, it discusses the cultural implications of this process in terms of both the nature and flow of creativity. Based on these analyses, the article also sheds light on the interplay between the state and the market in the context of globalisation and marketisation of media sectors, which becomes more complicated when the state-owned or controlled media enter the emerging market sectors.

Predicting movie ratings from audience behaviors

We propose a method of representing audience behavior through facial and body motions from a single video stream, and use these features to predict the rating for feature-length movies. This is a very challenging problem as: i) the movie viewing environment is dark and contains views of people at different scales and viewpoints; ii) the duration of feature-length movies is long (80-120 mins) so tracking people uninterrupted for this length of time is still an unsolved problem, and; iii) expressions and motions of audience members are subtle, short and sparse making labeling of activities unreliable. To circumvent these issues, we use an infrared illuminated test-bed to obtain a visually uniform input. We then utilize motion-history features which capture the subtle movements of a person within a pre-defined volume, and then form a group representation of the audience by a histogram of pair-wise correlations over a small-window of time. Using this group representation, we learn our movie rating classifier from crowd-sourced ratings collected by rottentomatoes.com and show our prediction capability on audiences from 30 movies across 250 subjects (> 50 hrs).

Why a movie tax will make even more of us pirates

In a nation of rampant illegal downloaders, a tax on movies and television downloads is the last thing we need. Australian consumers and content producers are among those likely to be worse off should Joe Hockey succeed in his efforts to extend GST to online video-on-demand services like Netflix. It is easy to see why Mr Hockey and his state treasurer counterparts have reportedly agreed to this move. That doesn’t mean it’s a good idea.

Undead yakuza: The Japanese zombie movie, cultural resonance and generic conventions

The zombie has long been regarded as a “fundamentally American creation” (Bishop 2010) and a western monster representing the fears and anxieties of Western society. Since the renaissance of the zombie movie in the early 2000s, a subsequent surge in international production has seen the release of movies from Norway, Cuba, Pakistan and Thailand to name a few. Although Japanese zombie movies have been far more visible for Western cult audiences than in mainstream markets, Japanese cinema has emerged as one of the more prolific producers of zombie films outside of Anglophone or Western European countries in recent years. Films such as Helldriver (2010), Zombie TV (2013), Versus (2000), Tokyo Zombie (2005), Happiness of the Katakuris (2001) and anime television series High School of the Dead (2010) have generated varying degrees of popularity and critical attention internationally. At first glance Japanese zombie films, with musical zombie interludes, undead yakuza henchmen and revenge-seeking yūrei zombies, appear fundamentally different to their Western counterparts. Yet, on closer examination, the Japanese zombie movie could be regarded as a hybrid and intertextual generic form drawing on syntactic conventions at the core of a universal zombie sub-genre established by Western filmmaking traditions, while also distilling culturally specific tropes unique to various Japanese horror cinema sub-genres. Most importantly, the Japanese zombie film extracts, emphasises and revises particular conventions and motifs common within Western zombie films that are particularly relevant to Japanese audiences. This chapter investigates the cultural resonance of key generic motifs identifiable in the Japanese zombie film. It establishes a production context and the influence of Japanese horror cinema on style and thematic concerns. It then examines the function of prominent narrative conventions, namely: the source, outbreak and spread of infection; mutation and the representation of the monster; and the inclusion of supernatural and religious motifs.

Alfred Lichtenstein making a movie; Berlin.

Digital Image

Alfred Lichtenstein making a movie; Berlin.

Digital Image

Efficacy of nano-silver in alleviating bacteria-related blockage in cut rose cv. Movie Star stems

Postharvest treatments with nano-silver (NS) significantly improve water relations and therefore prolong the vase life of several cut flowers, including rose (Rosa hybrida cv. Movie Star). The efficacy of NS in alleviating bacterial related blockage in the stem-ends of cut cv. Movie Star was further investigated. Four dominant bacteria strains Pseudomonas fluorescens, Aeromonas sp., Comamonas acidovorans and Chryseomonas luteola were isolated from the stem-ends of cut roses. High numbers of the isolated bacteria at 10 8colony forming unitsmL -1 vase solution led to a sharp reduction in vase life, flower fresh weight, and water uptake. In vitro assessments of the antibacterial activity of NS against the four bacterial strains was >80% at 5mgL -1 and nearly 100% at 50mgL -1. Bacterial blockage in the stem-ends of cut cv. Movie Star roses with and without NS pulse treatments was assessed during the vase period using scanning electron microscopy. Following a 50mgL -1 NS pulse treatment, there were few bacterial cells on the cut surface of the stems even on day 7. Moreover, no obvious bacterial blockage was observed inside the xylem vessels. In contrast, the cut surface of control stems was covered with bacteria and associated amorphous substances, and numerous bacteria were found in the xylem vessels. © 2012 Elsevier B.V.

Automatic phonetic transcription of Tamil in Roman script

Simple formalized rules are proposed for automatic phonetic transcription of Tamil words into Roman script. These rules are syntax-directed and require a one-symbol look-ahead facility and hence easily automated in a digital computer. Some suggestions are also put forth for the linearization of Tamil script for handling these by modern machinery.

A blind indic script recognizer for multi-script documents

We report a hierarchical blind script identifier for 11 different Indian scripts. An initial grouping of the 11 scripts is accomplished at the first level of this hierarchy. At the subsequent level, we recognize the script in each group. The various nodes of this tree use different feature-classifier combinations. A database of 20,000 words of different font styles and sizes is collected and used for each script. Effectiveness of Gabor and Discrete Cosine Transform features has been independently, evaluated using nearest neighbor linear discriminant and support vector machine classifiers. The minimum and maximum accuracies obtained, using this hierarchical mechanism, are 92.2% and 97.6%, respectively.

Online Handwriting Recognition of Tamil Script Using Fractal Geometry

We present a fractal coding method to recognize online handwritten Tamil characters and propose a novel technique to increase the efficiency in terms of time while coding and decoding. This technique exploits the redundancy in data, thereby achieving better compression and usage of lesser memory. It also reduces the encoding time and causes little distortion during reconstruction. Experiments have been conducted to use these fractal codes to classify the online handwritten Tamil characters from the IWFHR 2006 competition dataset. In one approach, we use fractal coding and decoding process. A recognition accuracy of 90% has been achieved by using DTW for distortion evaluation during classification and encoding processes as compared to 78% using nearest neighbor classifier. In other experiments, we use the fractal code, fractal dimensions and features derived from fractal codes as features in separate classifiers. While the fractal code is successful as a feature, the other two features are not able to capture the wide within-class variations.

MAST: multi-script annotation toolkit for scenic text

This paper describes a semi-automatic tool for annotation of multi-script text from natural scene images. To our knowledge, this is the maiden tool that deals with multi-script text or arbitrary orientation. The procedure involves manual seed selection followed by a region growing process to segment each word present in the image. The threshold for region growing can be varied by the user so as to ensure pixel-accurate character segmentation. The text present in the image is tagged word-by-word. A virtual keyboard interface has also been designed for entering the ground truth in ten Indic scripts, besides English. The keyboard interface can easily be generated for any script, thereby expanding the scope of the toolkit. Optionally, each segmented word can further be labeled into its constituent characters/symbols. Polygonal masks are used to split or merge the segmented words into valid characters/symbols. The ground truth is represented by a pixel-level segmented image and a '.txt' file that contains information about the number of words in the image, word bounding boxes, script and ground truth Unicode. The toolkit, developed using MATLAB, can be used to generate ground truth and annotation for any generic document image. Thus, it is useful for researchers in the document image processing community for evaluating the performance of document analysis and recognition techniques. The multi-script annotation toolokit (MAST) is available for free download.

Multi-script and multi-oriented text localization from scene images

This paper describes a new method of color text localization from generic scene images containing text of different scripts and with arbitrary orientations. A representative set of colors is first identified using the edge information to initiate an unsupervised clustering algorithm. Text components are identified from each color layer using a combination of a support vector machine and a neural network classifier trained on a set of low-level features derived from the geometric, boundary, stroke and gradient information. Experiments on camera-captured images that contain variable fonts, size, color, irregular layout, non-uniform illumination and multiple scripts illustrate the robustness of the method. The proposed method yields precision and recall of 0.8 and 0.86 respectively on a database of 100 images. The method is also compared with others in the literature using the ICDAR 2003 robust reading competition dataset.

Recognition of open vocabulary, online handwritten pages in Tamil script

In this work, we describe a system, which recognises open vocabulary, isolated, online handwritten Tamil words and extend it to recognize a paragraph of writing. We explain in detail each step involved in the process: segmentation, preprocessing, feature extraction, classification and bigram-based post-processing. On our database of 45,000 handwritten words obtained through tablet PC, we have obtained symbol level accuracy of 78.5% and 85.3% without and with the usage of post-processing using symbol level language models, respectively. Word level accuracies for the same are 40.1% and 59.6%. A line and word level segmentation strategy is proposed, which gives promising results of 100% line segmentation and 98.1% word segmentation accuracies on our initial trials of 40 handwritten paragraphs. The two modules have been combined to obtain a full-fledged page recognition system for online handwritten Tamil data. To the knowledge of the authors, this is the first ever attempt on recognition of open vocabulary, online handwritten paragraphs in any Indian language.

A Neural Network Model for Cursive Script Production

This article describes a neural network model, called the VITEWRITE model, for generating handwriting movements. The model consists of a sequential controller, or motor program, that interacts with a trajectory generator to move a. hand with redundant degrees of freedom. The neural trajectory generator is the Vector Integration to Endpoint (VITE) model for synchronous variable-speed control of multijoint movements. VITE properties enable a simple control strategy to generate complex handwritten script if the hand model contains redundant degrees of freedom. The proposed controller launches transient directional commands to independent hand synergies at times when the hand begins to move, or when a velocity peak in a given synergy is achieved. The VITE model translates these temporally disjoint synergy commands into smooth curvilinear trajectories among temporally overlapping synergetic movements. The separate "score" of onset times used in most prior models is hereby replaced by a self-scaling activity-released "motor program" that uses few memory resources, enables each synergy to exhibit a unimodal velocity profile during any stroke, generates letters that are invariant under speed and size rescaling, and enables effortless. connection of letter shapes into words. Speed and size rescaling are achieved by scalar GO and GRO signals that express computationally simple volitional commands. Psychophysical data concerning band movements, such as the isochrony principle, asymmetric velocity profiles, and the two-thirds power law relating movement curvature and velocity arise as emergent properties of model interactions.