Importance driven environment map sampling

In this paper we present an automatic and efficient method for supporting Image Based Lighting (IBL) for bidirectional methods which improves both the sampling of the environment, and the detection and sampling of important regions of the scene, such as windows and doors. These often have a small area proportional to that of the entire scene, so paths which pass through them are generated with a low probability. The method proposed in this paper improves this by taking into account view importance, and modifies the lighting distribution to use light transport information. This also automatically constructs a sampling distribution in locations which are relevant to the camera position, thereby improving sampling. Results are presented when our method is applied to bidirectional rendering techniques, in particular we show results for Bidirectional Path Tracing, Metropolis Light Transport and Progressive Photon Mapping. Efficiency results demonstrate speed up of orders of magnitude (depending on the rendering method used), when compared to other methods

An endogenous crepuscular rhythm of rainbow trout (Salmo gairdneri) photomechanical movements

1. The position of the epithelial pigment and cones in the retina of Salmo gairdneri was determined during extended periods of darkness in fish entrained to both artificial and natural light/dark cycles. 2. An endogenous rhythm of such photomechanical movements, unique among species so far examined, was observed in both groups of fish, with two peaks of light adaptation coincident with dawn and dusk. 3. It is suggested that such an apparently non-adaptive physiological rhythm is related to the behavioural pattern of trout and reveals a basic crepuscular organisation. 4. No endogenous rhythm was observed in continual light. 5. These results suggest that control of photomechanical changes in rainbow trout has two components: an endogenous component, that causes the bimodal pattern in maintained darkness, and a direct effect of light, that maintains light adaptation throughout a normal day

Using heterogeneous satellites for passive detection of moving aerial target

Passive detection of a moving aerial target is critical for intelligent surveillance. Its implementation can use signals transmitted from satellites. Nowadays, various types of satellites co-exist which can be used for passive detection. As a result, a satellite signal receiver may receive signals from multiple heterogeneous satellites, causing difficult in echo signal detection. In this paper, a passive moving aerial target detection method leveraging signals from multiple heterogeneous satellites is proposed. In the proposed method, a plurality of direct wave signals is separated in a reference channel first. Then, an adaptive filter with normalized least-mean-square (NLMS) is adopted to suppress direct-path interference (DPI) and multi-path interference (MPI) in a surveillance channel. Next, the maximum values of the cross ambiguity function (CAF) and the fourth order cyclic cumulants cross ambiguity function (FOCCCAF) correspond into each separated direct wave signal and echo signal will be utilized as the detection statistic of each distributed sensor. Finally, final detection probabilities are calculated by decision fusion based on results from distributed sensors. To evaluate the performance of the proposed method, extensive simulation studies are conducted. The corresponding simulation results show that the proposed fusion detection method can significantly improve the reliability of moving aerial target detection using multiple heterogeneous satellites. Moveover, we also show that the proposed detection method is able to significantly improve the detection performance by using multiple collaborative heterogeneous satellites