Person re-identification using group information

After first observing a person, the task of person re-identification involves recognising an individual at different locations across a network of cameras at a later time. Traditionally, this task has been performed by first extracting appearance features of an individual and then matching these features to the previous observation. However, identifying an individual based solely on appearance can be ambiguous, particularly when people wear similar clothing (i.e. people dressed in uniforms in sporting and school settings). This task is made more difficult when the resolution of the input image is small as is typically the case in multi-camera networks. To circumvent these issues, we need to use other contextual cues. In this paper, we use "group" information as our contextual feature to aid in the re-identification of a person, which is heavily motivated by the fact that people generally move together as a collective group. To encode group context, we learn a linear mapping function to assign each person to a "role" or position within the group structure. We then combine the appearance and group context cues using a weighted summation. We demonstrate how this improves performance of person re-identification in a sports environment over appearance based-features.

A novel representation of bioacoustic events for content-based search in field audio data

Bioacoustic data can provide an important base for environmental monitoring. To explore a large amount of field recordings collected, an automated similarity search algorithm is presented in this paper. A region of an audio defined by frequency and time bounds is provided by a user; the content of the region is used to construct a query. In the retrieving process, our algorithm will automatically scan through recordings to search for similar regions. In detail, we present a feature extraction approach based on the visual content of vocalisations – in this case ridges, and develop a generic regional representation of vocalisations for indexing. Our feature extraction method works best for bird vocalisations showing ridge characteristics. The regional representation method allows the content of an arbitrary region of a continuous recording to be described in a compressed format.

The engagement of small to medium enterprises for managing waste in building retrofit projects

The market of building retrofits is increasingly more intensified as existing buildings are aging. The building retrofit projects involve existing buildings which impose constraints on stakeholders throughout the project process. They are also risky, complex, less predictable and difficult to be well planned with on-site waste becoming one of the critical issues. Small and Medium Enterprises (SMEs) carry out most of the work in retrofit projects as subcontractors, but they often do not have adequate resources to deal with the specific technical challenges and project risks related to waste. This paper first discusses the requirements of waste management in building retrofit projects considering specific project characteristics and work natures, and highlights the importance of involving SMEs in waste planning and management through an appropriate way. By utilizing semi-structured interviews, this research develops a process model for SMEs to be applied in waste management. A collaboration scenario is also developed for collaborative waste planning and management by SMEs as subcontractors and large companies as main contractors. Findings from the paper will promote coordination of project delivery and waste management in building retrofit projects, and improve the involvement and performance of SMEs in dealing with waste problems.