WiseEye: Next Generation Expandable and Programmable Camera Trap Platform for Wildlife Research.

The widespread availability of relatively cheap, reliable and easy to use digital camera traps has led to their extensive use for wildlife research, monitoring and public outreach. Users of these units are, however, often frustrated by the limited options for controlling camera functions, the generation of large numbers of images, and the lack of flexibility to suit different research environments and questions. We describe the development of a user-customisable open source camera trap platform named 'WiseEye', designed to provide flexible camera trap technology for wildlife researchers. The novel platform is based on a Raspberry Pi single-board computer and compatible peripherals that allow the user to control its functions and performance. We introduce the concept of confirmatory sensing, in which the Passive Infrared triggering is confirmed through other modalities (i.e. radar, pixel change) to reduce the occurrence of false positives images. This concept, together with user-definable metadata, aided identification of spurious images and greatly reduced post-collection processing time. When tested against a commercial camera trap, WiseEye was found to reduce the incidence of false positive images and false negatives across a range of test conditions. WiseEye represents a step-change in camera trap functionality, greatly increasing the value of this technology for wildlife research and conservation management.

Limitations of recreational camera traps for wildlife management and conservation research: a practitioner's perspective.

The availability of affordable 'recreational' camera traps has dramatically increased over the last decade. We present survey results which show that many conservation practitioners use cheaper 'recreational' units for research rather than more expensive 'professional' equipment. We present our perspective of using two popular models of 'recreational' camera trap for ecological field-based studies. The models used (for >2 years) presented us with a range of practical problems at all stages of their use including deployment, operation, and data management, which collectively crippled data collection and limited opportunities for quantification of key issues arising. Our experiences demonstrate that prospective users need to have a sufficient understanding of the limitations camera trap technology poses, dimensions we communicate here. While the merits of different camera traps will be study specific, the performance of more expensive 'professional' models may prove more cost-effective in the long-term when using camera traps for research.

Embedded multiple description coding of video.

Real-time delivery of video over best-effort error-prone packet networks requires scalable erasure-resilient compression systems in order to 1) meet the users' requirements in terms of quality, resolution, and frame-rate; 2) dynamically adapt the rate to the available channel capacity; and 3) provide robustness to data losses, as retransmission is often impractical. Furthermore, the employed erasure-resilience mechanisms should be scalable in order to adapt the degree of resiliency against transmission errors to the varying channel conditions. Driven by these constraints, we propose in this paper a novel design for scalable erasure-resilient video coding that couples the compression efficiency of the open-loop architecture with the robustness provided by multiple description coding. In our approach, scalability and packet-erasure resilience are jointly provided via embedded multiple description scalar quantization. Furthermore, a novel channel-aware rate-allocation technique is proposed that allows for shaping on-the-fly the output bit rate and the degree of resiliency without resorting to channel coding. As a result, robustness to data losses is traded for better visual quality when transmission occurs over reliable channels, while erasure resilience is introduced when noisy links are involved. Numerical results clearly demonstrate the advantages of the proposed approach over equivalent codec instantiations employing 1) no erasure-resilience mechanisms, 2) erasure-resilience with nonscalable redundancy, or 3) data-partitioning principles.