Periodic Motion Detection and Estimation via Space-Time Sampling

A novel technique to detect and localize periodic movements in video is presented. The distinctive feature of the technique is that it requires neither feature tracking nor object segmentation. Intensity patterns along linear sample paths in space-time are used in estimation of period of object motion in a given sequence of frames. Sample paths are obtained by connecting (in space-time) sample points from regions of high motion magnitude in the first and last frames. Oscillations in intensity values are induced at time instants when an object intersects the sample path. The locations of peaks in intensity are determined by parameters of both cyclic object motion and orientation of the sample path with respect to object motion. The information about peaks is used in a least squares framework to obtain an initial estimate of these parameters. The estimate is further refined using the full intensity profile. The best estimate for the period of cyclic object motion is obtained by looking for consensus among estimates from many sample paths. The proposed technique is evaluated with synthetic videos where ground-truth is known, and with American Sign Language videos where the goal is to detect periodic hand motions.

Limitations of instantaneous water quality sampling in surface-water catchments: Comparison with near-continuous phosphorus time-series data.

The validity of load estimates from intermittent, instantaneous grab sampling is dependent on adequate spatial coverage by monitoring networks and a sampling frequency that re?ects the variability in the system under study. Catchments with a ?ashy hydrology due to surface runoff pose a particular challenge as intense short duration rainfall events may account for a signi?cant portion of the total diffuse transfer of pollution from soil to water in any hydrological year. This can also be exacerbated by the presence of strong background pollution signals from point sources during low flows. In this paper, a range of sampling methodologies and load estimation techniques are applied to phosphorus data from such a surface water dominated river system, instrumented at three sub-catchments (ranging from 3 to 5 km2 in area) with near-continuous monitoring stations. Systematic and Monte Carlo approaches were applied to simulate grab sampling using multiple strategies and to calculate an estimated load, Le based on established load estimation methods. Comparison with the actual load, Lt, revealed signi?cant average underestimation, of up to 60%, and high variability for all feasible sampling approaches. Further analysis of the time series provides an insight into these observations; revealing peak frequencies and power-law scaling in the distributions of P concentration, discharge and load associated with surface runoff and background transfers. Results indicate that only near-continuous monitoring that re?ects the rapid temporal changes in these river systems is adequate for comparative monitoring and evaluation purposes. While the implications of this analysis may be more tenable to small scale ?ashy systems, this represents an appropriate scale in terms of evaluating catchment mitigation strategies such as agri-environmental policies for managing diffuse P transfers in complex landscapes.

Adaptive, Decentralized, And Real-Time Sampling Strategies For Resource Constrained Hydraulic And Hydrologic Sensor Networks

We discuss the development and performance of a low-power sensor node (hardware, software and algorithms) that autonomously controls the sampling interval of a suite of sensors based on local state estimates and future predictions of water flow. The problem is motivated by the need to accurately reconstruct abrupt state changes in urban watersheds and stormwater systems. Presently, the detection of these events is limited by the temporal resolution of sensor data. It is often infeasible, however, to increase measurement frequency due to energy and sampling constraints. This is particularly true for real-time water quality measurements, where sampling frequency is limited by reagent availability, sensor power consumption, and, in the case of automated samplers, the number of available sample containers. These constraints pose a significant barrier to the ubiquitous and cost effective instrumentation of large hydraulic and hydrologic systems. Each of our sensor nodes is equipped with a low-power microcontroller and a wireless module to take advantage of urban cellular coverage. The node persistently updates a local, embedded model of flow conditions while IP-connectivity permits each node to continually query public weather servers for hourly precipitation forecasts. The sampling frequency is then adjusted to increase the likelihood of capturing abrupt changes in a sensor signal, such as the rise in the hydrograph – an event that is often difficult to capture through traditional sampling techniques. Our architecture forms an embedded processing chain, leveraging local computational resources to assess uncertainty by analyzing data as it is collected. A network is presently being deployed in an urban watershed in Michigan and initial results indicate that the system accurately reconstructs signals of interest while significantly reducing energy consumption and the use of sampling resources. We also expand our analysis by discussing the role of this approach for the efficient real-time measurement of stormwater systems.

Influence of carrion smell and rebaiting time on the efficiency of pitfall traps to dung beetle sampling

Dung beetles (Coleoptera: Scarabaeidae: Scarabaeinae) are very useful insects, as they improve the chemo-physical properties of soil, clean pastures from dung pads, and help control symbovine flies associated with bovine cattle. Their importance makes it fundamental to sample and survey them adequately. The objectives of the present study were to determine the influence of decaying insects trapped in pitfalls on the attractiveness of Moura pig Sus scrofa L. (Suidae) and collared peccary Tayassu tajacu (L.) (Tayassuidae) dung used as baits to lure dung beetles, and to establish how long these baits remain attractive to dung beetles when used in these traps. Some dung beetle species seemed to be able to discriminate against foul smell from decaying insects within the first 24 h, hence decreasing trap efficiency. This was more evident in peccary dung-baited traps, which proved to be the least attractive bait. Attractiveness lasted only 24 h for peccary dung, after which it became unattractive, whereas the pig dung bait was highly attractive for 48 h, after which its attractiveness diminished but was not completely lost.

Real-time Sampling of Particulate Matter Smaller than 2.5 µm from Amazon Forest Biomass Combustion

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Asynchronous ECG time sampling: Saving bits with Golomb-Rice encoding

We present a technique for online compression of ECG signals using the Golomb-Rice encoding algorithm. This is facilitated by a novel time encoding asynchronous analog-to-digital converter targeted for low-power, implantable, long-term bio-medical sensing applications. In contrast to capturing the actual signal (voltage) values the asynchronous time encoder captures and encodes the time information at which predefined changes occur in the signal thereby minimizing the sensor's energy use and the number of bits we store to represent the information by not capturing unnecessary samples. The time encoder transforms the ECG signal data to pure time information that has a geometric distribution such that the Golomb-Rice encoding algorithm can be used to further compress the data. An overall online compression rate of about 6 times is achievable without the usual computations associated with most compression methods.

Evaluation of the effectiveness of enrichment for a group of captive squirrel monkeys (Saimiri sciureus) using time-lapse recording and instantaneous scan sampling

One aim of providing enrichment to captive animals is to promote the expression of behavioural patterns similar to their wild conspecifics. We evaluated the effectiveness of four types of simple feeding enrichment, using surveillance cameras to record the behaviour of 11 captive squirrel monkeys housed in a single enclosure at Alma Park Zoo in Brisbane, Australia. The enrichment involved differences in presentation (whole/chopped) and distribution (localised/scattered) of fruit and vegetables that were part of the normal diet of these animals. Distinguishing between individual squirrel monkeys was not possible from the videos, so Instantaneous Scan Sampling was used to record the numbers of animals performing particular behaviours every 15 minutes over the 24 hour period as well as every 5 minutes for the hour following provision of enrichment. This provided an estimation of the percentage of time spent by the group in various activities. As a result of the enrichment, the activity budget of the group more closely approximated that of wild squirrel monkeys. However on a number of occasions where the enrichment required the squirrel monkeys to work to obtain their food (whole fruit and vegetables), a number of individuals became aggressive towards the zookeepers. This result highlights the variation in responses of individual animals towards enrichment and indicates that in enclosures with large numbers of animals, the response of each individual should be evaluated in addition to the overall benefit of the enrichment for the group. Furthermore, this variation also suggests that it may be beneficial to provide the animals with choices of enrichment as opposed to providing single forms of enrichment that may only be effective for a proportion of the animals in the enclosure, and may even result in undesirable responses from some individuals.