Crowd counting using group tracking and local features

In public venues, crowd size is a key indicator of crowd safety and stability. In this paper we propose a crowd counting algorithm that uses tracking and local features to count the number of people in each group as represented by a foreground blob segment, so that the total crowd estimate is the sum of the group sizes. Tracking is employed to improve the robustness of the estimate, by analysing the history of each group, including splitting and merging events. A simplified ground truth annotation strategy results in an approach with minimal setup requirements that is highly accurate.

Virtual product placement as a new approach to measure effectiveness of placements

Product placement is a fast growing multi-billion dollar industry yet measures of its effectiveness, which influence the critical area of pricing, have been problematic. Past attempts to measure the effect of a placement, and therefore provide a basis for pricing of placements, have been confounded by the effect on consumers of multiple prior exposures of a brand name in all marketing communications. Virtual product placement offers certain advantages: as a tool to measure the effectiveness of product placements; assistance with the problem of lack of audience selectivity in traditional product placement; testing different audiences for brands and addressing a gap in the existing academic literature by focusing on the impact of product placement on recall and recognition of new brands.

The impact of brand and product placements in electronic games

In an environment where it has become increasingly difficult to attract consumer attention, marketers have begun to explore alternative forms of marketing communication. One such form that has emerged is product placement, which has more recently appeared in electronic games. Given changes in media consumption and the growth of the games industry, it is not surprising that games are being exploited as a medium for promotional content. Other market developments are also facilitating and encouraging their use, in terms of both the insertion of brand messages into video games and the creation of brand-centred environments, labelled ���advergames���. However, while there is much speculation concerning the beneficial outcomes for marketers, there remains a lack of academic work in this area and little empirical evidence of the actual effects of this form of promotion on game players. Only a handful of studies are evident in the literature, which have explored the influence of game placements on consumers. The majority have studied their effect on brand awareness, largely demonstrating that players can recall placed brands. Further, most research conducted to date has focused on computer and online games, but consoles represent the dominant platform for play (Taub, 2004). Finally, advergames have largely been neglected, particularly those in a console format. Widening the gap in the literature is the fact that insufficient academic attention has been given to product placement as a marketing communication strategy overall, and to games in general. The unique nature of the strategy also makes it difficult to apply existing literature to this context. To address a significant need for information in both the academic and business domains, the current research investigates the effects of brand and product placements in video games and advergames on consumer attitude to the brand and corporate image. It was conducted in two stages. Stage one represents a pilot study. It explored the effects of use simulated and peripheral placements in video games on players��� and observers��� attitudinal responses, and whether these are influenced by involvement with a product category or skill level in the game. The ability of gamers to recall placed brands was also examined. A laboratory experiment was employed with a small sample of sixty adult subjects drawn from an Australian east-coast university, some of who were exposed to a console video game on a television set. The major finding of study one is that placements in a video game have no effect on gamers��� attitudes, but they are recalled. For stage two of the research, a field experiment was conducted with a large, random sample of 350 student respondents to investigate the effects on players of brand and product placements in handheld video games and advergames. The constructs of brand attitude and corporate image were again tested, along with several potential confounds. Consistent with the pilot, the results demonstrate that product placement in electronic games has no effect on players��� brand attitudes or corporate image, even when allowing for their involvement with the product category, skill level in the game, or skill level in relation to the medium. Age and gender also have no impact. However, the more interactive a player perceives the game to be, the higher their attitude to the placed brand and corporate image of the brand manufacturer. In other words, when controlling for perceived interactivity, players experienced more favourable attitudes, but the effect was so weak it probably lacks practical significance. It is suggested that this result can be explained by the existence of excitation transfer, rather than any processing of placed brands. The current research provides strong, empirical evidence that brand and product placements in games do not produce strong attitudinal responses. It appears that the nature of the game medium, game playing experience and product placement impose constraints on gamer motivation, opportunity and ability to process these messages, thereby precluding their impact on attitude to the brand and corporate image. Since this is the first study to investigate the ability of video game and advergame placements to facilitate these deeper consumer responses, further research across different contexts is warranted. Nevertheless, the findings have important theoretical and managerial implications. This investigation makes a number of valuable contributions. First, it is relevant to current marketing practice and presents findings that can help guide promotional strategy decisions. It also presents a comprehensive review of the games industry and associated activities in the marketplace, relevant for marketing practitioners. Theoretically, it contributes new knowledge concerning product placement, including how it should be defined, its classification within the existing communications framework, its dimensions and effects. This is extended to include brand-centred entertainment. The thesis also presents the most comprehensive analysis available in the literature of how placements appear in games. In the consumer behaviour discipline, the research builds on theory concerning attitude formation, through application of MacInnis and Jaworski���s (1989) Integrative Attitude Formation Model. With regards to the games literature, the thesis provides a structured framework for the comparison of games with different media types; it advances understanding of the game medium, its characteristics and the game playing experience; and provides insight into console and handheld games specifically, as well as interactive environments generally. This study is the first to test the effects of interactivity in a game environment, and presents a modified scale that can be used as part of future research. Methodologically, it addresses the limitations of prior research through execution of a field experiment and observation with a large sample, making this the largest study of product placement in games available in the literature. Finally, the current thesis offers comprehensive recommendations that will provide structure and direction for future study in this important field.

Vision-based classification of solder joint defects

Inspection of solder joints has been a critical process in the electronic manufacturing industry to reduce manufacturing cost, improve yield, and ensure product quality and reliability. The solder joint inspection problem is more challenging than many other visual inspections because of the variability in the appearance of solder joints. Although many research works and various techniques have been developed to classify defect in solder joints, these methods have complex systems of illumination for image acquisition and complicated classification algorithms. An important stage of the analysis is to select the right method for the classification. Better inspection technologies are needed to fill the gap between available inspection capabilities and industry systems. This dissertation aims to provide a solution that can overcome some of the limitations of current inspection techniques. This research proposes two inspection steps for automatic solder joint classification system. The ���front-end��� inspection system includes illumination normalisation, localization and segmentation. The illumination normalisation approach can effectively and efficiently eliminate the effect of uneven illumination while keeping the properties of the processed image. The ���back-end��� inspection involves the classification of solder joints by using Log Gabor filter and classifier fusion. Five different levels of solder quality with respect to the amount of solder paste have been defined. Log Gabor filter has been demonstrated to achieve high recognition rates and is resistant to misalignment. Further testing demonstrates the advantage of Log Gabor filter over both Discrete Wavelet Transform and Discrete Cosine Transform. Classifier score fusion is analysed for improving recognition rate. Experimental results demonstrate that the proposed system improves performance and robustness in terms of classification rates. This proposed system does not need any special illumination system, and the images are acquired by an ordinary digital camera. In fact, the choice of suitable features allows one to overcome the problem given by the use of non complex illumination systems. The new system proposed in this research can be incorporated in the development of an automated non-contact, non-destructive and low cost solder joint quality inspection system.

Dynamic visual features for audio-visual speaker verification

The cascading appearance-based (CAB) feature extraction technique has established itself as the state-of-the-art in extracting dynamic visual speech features for speech recognition. In this paper, we will focus on investigating the effectiveness of this technique for the related speaker verification application. By investigating the speaker verification ability of each stage of the cascade we will demonstrate that the same steps taken to reduce static speaker and environmental information for the visual speech recognition application also provide similar improvements for visual speaker recognition. A further study is conducted comparing synchronous HMM (SHMM) based fusion of CAB visual features and traditional perceptual linear predictive (PLP) acoustic features to show that higher complexity inherit in the SHMM approach does not appear to provide any improvement in the final audio-visual speaker verification system over simpler utterance level score fusion.

Positive relationships among collaboration for innovation, past innovation abandonment and future product introduction in manufacturing SMEs

The importance of collaboration for firm level innovation has been well established but much of the research focuses on large firms, with little research on small and medium enterprises. This paper investigates the links between product innovation and external collaboration and between future product innovation and past abandonment in small and medium sized firms, analysing data from 449 manufacturing firms, collected through the Australian Business Longitudinal Database. Our findings indicate firms that sought ideas or solutions from external network such as suppliers, or business partners reported higher level of new product introduction than firms that did not have any external collaboration. Further, firms with past abandonment experiences reported higher levels of new product introduction than firms that did not have such experience. Additionally, the findings indicated that firms with external collaboration were more likely to introduce new products even if they had previously experienced abandonment of a product innovation than firms without external collaboration. Implications, limitations and future research are outlined.

Sustainable urban stormwater management : water sensitive urban design perceptions, drivers and barriers

Stormwater has been recognised as one of the main culprits of aquatic ecosystem pollution and as a significant threat to the goal of ecological sustainable development. Water sensitive urban design is one of the key responses to the need to better manage urban stormwater runoff, the objectives of which go beyond rapid and efficient conveyance. Underpinned by the concepts of sustainable urban development, water sensitive urban design has proven to be an efficient and environmentally-friendly approach to urban stormwater management, with the necessary technical know-how and skills already available. However, large-scale implementation of water sensitive urban design is still lacking in Australia due to significant impediments and negative perceptions. Identification of the issues, barriers and drivers that affect sustainability outcomes of urban stormwater management is one of the first steps towards encouraging the wide-scale uptake of water sensitive urban design features which integrate sustainable urban stormwater management. This chapter investigates key water sensitive urban design perceptions, drivers and barriers in order to improve sustainable urban stormwater management efforts.

Evaluation of spectral and texture features for object-based vegetation species classification using Support Vector Machines

The use of appropriate features to characterize an output class or object is critical for all classification problems. This paper evaluates the capability of several spectral and texture features for object-based vegetation classification at the species level using airborne high resolution multispectral imagery. Image-objects as the basic classification unit were generated through image segmentation. Statistical moments extracted from original spectral bands and vegetation index image are used as feature descriptors for image objects (i.e. tree crowns). Several state-of-art texture descriptors such as Gray-Level Co-Occurrence Matrix (GLCM), Local Binary Patterns (LBP) and its extensions are also extracted for comparison purpose. Support Vector Machine (SVM) is employed for classification in the object-feature space. The experimental results showed that incorporating spectral vegetation indices can improve the classification accuracy and obtained better results than in original spectral bands, and using moments of Ratio Vegetation Index obtained the highest average classification accuracy in our experiment. The experiments also indicate that the spectral moment features also outperform or can at least compare with the state-of-art texture descriptors in terms of classification accuracy.