Accelerometers, Ground Truthing, and Supervised Learning
Accelerometers are sensitive to movement and the lack of it. They are not sentient and must recognise animal behaviour based on a human observer’s cognition. Therefore, remote recognition of behaviour using accelerometers requires ground truth data which is based on human observation or knowledge. The need for validated behavioural information and for automating the analysis of the vast amounts of data collected today, have resulted in many studies opting for supervised machine learning approaches.
Ground-truthing. The acceleration data stream (recorded using the animal-borne data logger, bottom-left) is synchronised with simultaneously recorded video (near top right). Picture credit: Kamiar Aminian
In such approaches, the process of ground truthing involves time-synchronising acceleration signals with simultaneously recorded video, having an animal behaviour expert create an ethogram, and then annotate the video according to this ethogram. This links the recorded acceleration signal to the stream of observed animal behaviours that produced it. After this, acceleration signals are chopped up into finite sections of pre-set size (e.g. two seconds), called windows. From acceleration data within windows, quantities called ‘features’ are engineered with the aim of summarising characteristics of the acceleration signal. Typically, ~15-20 features are computed. Good features will have similar values for the same behaviour, and different values for different behaviours.
It’s more important than ever for us to have accurate information to help marine conservation efforts. Jordan Goetze and his colleagues have provided the first comprehensive guide for researchers using diver operated stereo-video methods (or stereo-DOVs) to survey fish assemblages and their associated habitat. But what is Stereo DOV? What makes it a better method than the traditional UVC (Underwater Visual Census) method? And when … Continue reading Stereo DOV: A Non-Invasive, Non-Destructive Way to Study Fish Populations
Quantifying animal movement is central to research spanning a variety of topics. It’s an important area of study for behavioural ecologists, evolutionary biologists, ecotoxicologists and many more. There are a lot of ways to track animals, but they’re often difficult, especially for people who don’t have a strong background in programming. Vivek Hari Sridhar, Dominique G. Roche and Simon Gingins have developed a new, simple software to … Continue reading Quantifying Animal Movement from Videos
Anyone who studies social animals in the wild (or human groups, for that matter), will soon find that some individuals threaten or attack others frequently, while others try to get out of the way or signal their submission in response to aggression. Observers tally the outcome of such aggressive interactions between any given two individuals (or ‘dyads’) and try to deduce the rank hierarchy from such winner-loser matrices. One drawback of this approach is that all temporal information is lost.
Imagine Royal, a baboon, dominating over Power, another baboon, 20 times, and Power dominating over Royal 20 times as well. If we just look at these data, we might think that they have the same fighting ability and similar ranks. But, if we know that Royal beat Power the first 20 of the interactions, then Power beat Royal in all further interactions, we’d come to a totally different conclusion. We’d infer that Power had toppled Royal and a rank change had taken place.
Motion vision is an important source of information for many animals. It facilitates an animal’s movement through an environment, as well as being essential for locating prey and detecting predators. However, information on the conditions for motion vision in natural environments is limited. To address this, Bian et al. have developed an innovative approach that combines novel field techniques with tools from 3D animation to … Continue reading Animal Behaviour through a Virtual Lens
Many animals rely on movement to find prey and avoid predators. Movement is also an essential component of the territorial displays of lizards, comprising tail, limb, head and whole-body movements.
For the first time, digital animation has been used as a research tool to examine how the effectiveness of a lizard’s territorial display varies across ecological environments and conditions. The new research was published today in the journal Methods in Ecology and Evolution.
Post provided by THEONI PHOTOPOULOU, MEGAN MURGATROYD, VIANEY LEOS-BARAJAS Around the world there are concerns over the impacts of land use change and the developments (such as wind farms). These concerns have led to the implementation of tracking studies to better understand movement patterns of animals. Such studies have provided a wealth of high-resolution data and opportunities to explore sophisticated statistical methods for analysis of animal behaviour. We use … Continue reading Soaring with Eagles, Swimming with Sharks: Measuring Animal Behaviour with Hidden Markov Models
“I am broadly interested in developing and applying statistical tools to infer behavioural and population processes from empirical data. My work tends to focus on marine and polar mammals, but the methods I develop are often applicable to a wide range of species and ecosystems. My recent work has centred on modelling animal behaviour using movement data and I generally analyse data with spatial and/or temporal structure.”
Methods Blog 