Path Reuse Research Articles

Lossless Basis Expansion for Gradient‐Domain Rendering

AbstractGradient‐domain rendering utilizes difference estimates with shift mapping to reduce variance in Monte Carlo rendering. Such difference estimates are effective under the assumption that pixels for difference estimates have similar integrands. This assumption is often violated because it is common to have spatially varying BSDFs with material maps, which potentially result in a very different integrand per pixel. We introduce an extension of gradient‐domain rendering that effectively supports such per‐pixel variation in BSDFs based on basis expansion. Basis expansion for BSDFs has been used extensively in other problems in rendering, where the goal is to approximate a given BSDF by a weighted sum of predefined basis functions. We instead utilize lossless basis expansion, representing a BSDF without any approximation by adding the remaining difference in the original basis expansion. This lossless basis expansion allows us to cancel more terms via shift mapping, resulting in low variance difference estimates even with per‐pixel BSDF variation. We also extend the Poisson reconstruction process to support this basis expansion. Regular gradient‐domain rendering can be expressed as a special case of our extension, where the basis is simply the BSDF per pixel (i.e., no basis expansion). We provide proof‐of‐concept experiments and showcase the effectiveness of our method for scenes with highly varying material maps. Our results show noticeable improvement over regular gradient‐domain rendering under both L1 and L2 reconstructions. The resulting formulation via basis expansion essentially serves as a new way of path reuse among pixels in the presence of per‐pixel variation.

Area ReSTIR: Resampling for Real-Time Defocus and Antialiasing

Recent advancements in spatiotemporal reservoir resampling (ReSTIR) leverage sample reuse from neighbors to efficiently evaluate the path integral. Like rasterization, ReSTIR methods implicitly assume a pinhole camera and evaluate the light arriving at a pixel through a single predetermined subpixel location at a time (e.g., the pixel center). This prevents efficient path reuse in and near pixels with high-frequency details. We introduce Area ReSTIR , extending ReSTIR reservoirs to also integrate each pixel's 4D ray space, including 2D areas on the film and lens. We design novel subpixel-tracking temporal reuse and shift mappings that maximize resampling quality in such regions. This robustifies ReSTIR against high-frequency content, letting us importance sample subpixel and lens coordinates and efficiently render antialiasing and depth of field.

Path Planning for 5-Axis CMM Inspection Considering Path Reuse

The 5-axis Coordinate Measuring Machine (CMM) is widely used for quality data collection of the machining parts, such as cylinder blocks and heads of the engines. High efficient inspection path planning for multiple feature groups from different stations is one of the key tasks for CMM application. In engineering practice, the inspection planning of diverse feature groups accounts for large labor cost and process development cycle. To improve the efficiency of path generation for the complex machining part, a five-axis CMM inspection path planning method considering path length, probe rotation and path reusability is proposed. Firstly, the measuring points (MPs) are classified based on feasible inspection direction cone and accessibility of the MPs to achieve the minimum times of probe rotation. Then, the rapidly exploring random trees with multi-root node (RRT-MRNC) algorithm is proposed to implement local path planning considering inspection path reuse. Furthermore, intra-group and inter-group path is generated simultaneously based on the proposed enhanced Genetic Algorithm (GA) algorithm. In order to evaluate the effectiveness of the proposed method, the cylinder block path planning case is used. Compared with the benchmark methods, the total planning time based on the proposed planning method for the dynamic tasks was reduced by 55.2% and 54.9% respectively.

Generalized resampled importance sampling

As scenes become ever more complex and real-time applications embrace ray tracing, path sampling algorithms that maximize quality at low sample counts become vital. Recent resampling algorithms building on Talbot et al.'s [2005] resampled importance sampling (RIS) reuse paths spatiotemporally to render surprisingly complex light transport with a few samples per pixel. These reservoir-based spatiotemporal importance resamplers (ReSTIR) and their underlying RIS theory make various assumptions, including sample independence. But sample reuse introduces correlation , so ReSTIR-style iterative reuse loses most convergence guarantees that RIS theoretically provides. We introduce generalized resampled importance sampling (GRIS) to extend the theory, allowing RIS on correlated samples, with unknown PDFs and taken from varied domains. This solidifies the theoretical foundation, allowing us to derive variance bounds and convergence conditions in ReSTIR-based samplers. It also guides practical algorithm design and enables advanced path reuse between pixels via complex shift mappings. We show a path-traced resampler (ReSTIR PT) running interactively on complex scenes, capturing many-bounce diffuse and specular lighting while shading just one path per pixel. With our new theoretical foundation, we can also modify the algorithm to guarantee convergence for offline renderers.

A Quantitative Framework for Identifying Patterns of Route-Use in Animal Movement Data

Animal movement along repeatedly used, “habitual” routes could emerge from a variety of cognitive mechanisms, as well as in response to a diverse set of environmental features. Because of the high conservation value of identifying wildlife movement corridors, there has been extensive work focusing on environmental factors that contribute to the emergence of habitual routes between protected habitats. In parallel, significant work has focused on disentangling the cognitive mechanisms underlying animal route use, as such movement patterns are of fundamental interest to the study of decision making and navigation. We reviewed the types of processes that can generate routine patterns of animal movement, suggested a new methodological workflow for classifying one of these patterns—high fidelity path reuse—in animal tracking data, and compared the prevalence of this pattern across four sympatric species of frugivorous mammals in Panama. We found the highest prevalence of route-use in kinkajous, the only nocturnal species in our study, and propose that further development of this method could help to distinguish the processes underlying the presence of specific routes in animal movement data.

Path graphs

To render higher quality images from the samples generated by path tracing with a low sample count, we propose a novel path reuse approach that processes a fixed collection of paths to iteratively refine and improve radiance estimates throughout the scene. Our method operates on a path graph consisting of the union of the traced paths with additional neighbor edges inserted among clustered nearby vertices. Our approach refines the initial noisy radiance estimates via an aggregation operator, treating vertices within clusters as independent sampling techniques that can be combined using MIS. In a novel step, we also introduce a propagation operator to forward the refined estimates along the paths to successive bounces. We apply the aggregation and propagation operations to the graph iteratively, progressively refining the radiance values, converging to fixed-point radiance estimates with lower variance than the original ones. We also introduce a decorrelation (final gather) step, which uses information already in the graph and is cheap to compute, allowing us to combine the method with standard denoisers. Our approach is lightweight, in the sense that it can be easily plugged into any standard path tracer and neural final image denoiser. Furthermore, it is independent of scene complexity, as the graph size only depends on image resolution and average path depth. We demonstrate that our technique leads to realistic rendering results starting from as low as 1 path per pixel, even in complex indoor scenes dominated by multi-bounce indirect illumination.

Hybrid Assembly Path Planning for Complex Products by Reusing a Priori Data

Assembly path planning (APP) for complex products is challenging due to the large number of parts and intricate coupling requirements. A hybrid assembly path planning method is proposed herein that reuses a priori paths to improve the efficiency and success ratio. The assembly path is initially segmented to improve its reusability. Subsequently, the planned assembly paths are employed as a priori paths to establish an a priori tree, which is expanded according to the bounding sphere of the part to create the a priori space for path searching. Three rapidly exploring random tree (RRT)-based algorithms are studied for path planning based on a priori path reuse. The RRT* algorithm establishes the new path exploration tree in the early planning stage when there is no a priori path to reuse. The static RRT* (S-RRT*) and dynamic RRT* (D-RRT*) algorithms form the connection between the exploration tree and the a priori tree with a pair of connection points after the extension of the exploration tree to a priori space. The difference between the two algorithms is that the S-RRT* algorithm directly reuses an a priori path and obtains a new path through static backtracking from the endpoint to the starting point. However, the D-RRT* algorithm further extends the exploration tree via the dynamic window approach to avoid collision between an a priori path and obstacles. The algorithm subsequently obtains a new path through dynamic and non-continuous backtracking from the endpoint to the starting point. A hybrid process combining the RRT*, S-RRT*, and D-RRT* algorithms is designed to plan the assembly path for complex products in several cases. The performances of these algorithms are compared, and simulations indicate that the S-RRT* and D-RRT* algorithms are significantly superior to the RRT* algorithm in terms of the efficiency and success ratio of APP. Therefore, hybrid path planning combining the three algorithms is helpful to improving the assembly path planning of complex products.

Rapid Planning of an Assembly Path by Reusing the Prior Path

Assembly path planning of complex products in virtual assembly is a necessary and complicated step, which will become long and inefficient if the assembly path of each part is completely planned in the assembly space. The coincidence or partial coincidence of the assembly paths of some parts provides an opportunity to solve this problem. A path planning algorithm based on prior path reuse (PPR algorithm) is proposed in this paper, which realizes rapid planning of an assembly path by reusing the planned paths. The core of the PPR algorithm is a dual-tree fusion strategy for path reuse, which is implemented by improving the rapidly exploring random tree star (RRT *) algorithm. The dual-tree fusion strategy is used to find the nearest prior node, the prior connection node, the nearest exploring node, and the exploring connection node and to connect the exploring tree to the prior tree after the exploring tree is extended to the prior space. Then, the optimal path selection strategy is used to calculate the costs of all planned paths and select the one with the minimum cost as the optimal path. The PPR algorithm is compared with the RRT * algorithm in path planning for one start node and multiple start nodes. The results show that the total time and the number of sampling points for assembly path planning of batch parts using the PPR algorithm are far less than those using the RRT * algorithm.

A fast algorithm for finding K shortest paths using generalized spur path reuse technique

AbstractThe problem of finding the K shortest paths (KSPs) between a pair of nodes in a road network is an important network optimization problem with broad applications. Yen's algorithm is a classical algorithm for exactly solving the KSP problem. However, it requires numerous shortest path searches, which can be computationally intensive for real large networks. This study proposes a fast algorithm by introducing a generalized spur path reuse technique. Using this technique, shortest paths calculated during the KSP finding process are stored. Accordingly, many shortest path searches can be avoided by reusing these stored paths. The results of computational experiments on several large‐scale road networks show that the introduced generalized spur path reuse technique can avoid more than 98% of shortest path searches in the KSP finding process. The proposed algorithm speeds up Yen's algorithm by up to 98.7 times in experimental networks.

Path reuse-aware routing for non-volatile memory based FPGAs

Non-volatile memory-based FPGAs (NV-FPGAs) are expected to replace traditional SRAM-based FPGAs to achieve higher scalability and lower power consumption. Yet the slow write performance of NVMs not only challenges FPGA reconfiguration speed and overhead but also constrains the programming cycles of FPGAs. To efficiently configure switch boxes, the majority component of an FPGA, this paper presents a routing path reuse technique. The reconfiguration cost of routing resources is first modeled mathematically and then minimized through a reuse-aware routing algorithm, which is incorporated into the standard VTR CAD tool. Experiments on standard MCNC and Titan benchmarks show that the proposed scheme is able to achieve as much as 58% path reuse rate and reduce as much as 45% configuration cost for routing resources.

Variance Analysis and Adaptive Sampling for Indirect Light Path Reuse

In this paper, we study the estimation variance of a set of global illumination algorithms based on indirect light path reuse. These algorithms usually contain two passes — in the first pass, a small number of indirect light samples are generated and evaluated, and they are then reused by a large number of reconstruction samples in the second pass. Our analysis shows that the covariance of the reconstruction samples dominates the estimation variance under high reconstruction rates and increasing the reconstruction rate cannot effectively reduce the covariance. We also find that the covariance represents to what degree the indirect light samples are reused during reconstruction. This analysis motivates us to design a heuristic approximating the covariance as well as an adaptive sampling scheme based on this heuristic to reduce the rendering variance. We validate our analysis and adaptive sampling scheme in the indirect light field reconstruction algorithm and the axis-aligned filtering algorithm for indirect lighting. Experiments are in accordance with our analysis and show that rendering artifacts can be greatly reduced at a similar computational cost.

Lizard movement tracks: variation in path re-use behaviour is consistent with a scent-marking function.

Individual movement influences the spatial and social structuring of a population. Animals regularly use the same paths to move efficiently to familiar places, or to patrol and mark home ranges. We found that Australian sleepy lizards (Tiliqua rugosa), a monogamous species with stable pair-bonds, repeatedly used the same paths within their home ranges and investigated whether path re-use functions as a scent-marking behaviour, or whether it is influenced by site familiarity. Lizards can leave scent trails on the substrate when moving through the environment and have a well-developed vomeronasal system to detect and respond to those scents. Path re-use would allow sleepy lizards to concentrate scent marks along these well-used trails, advertising their presence. Hypotheses of mate attraction and mating competition predict that sleepy lizard males, which experience greater intra-sexual competition, mark more strongly. Consistent with those hypotheses, males re-used their paths more than females, and lizards that showed pairing behaviour with individuals of the opposite sex re-used paths more than unpaired lizards, particularly among females. Hinterland marking is most economic when home ranges are large and mobility is low, as is the case in the sleepy lizard. Consistent with this strategy, re-used paths were predominantly located in the inner 50% home range areas. Together, our detailed movement analyses suggest that path re-use is a scent marking behaviour in the sleepy lizard. We also investigated but found less support for alternative explanations of path re-use behaviour, such as site familiarity and spatial knowledge. Lizards established the same number of paths, and used them as often, whether they had occupied their home ranges for one or for more years. We discuss our findings in relation to maintenance of the monogamous mating system of this species, and the spatial and social structuring of the population.

Path finding algorithm in massive multiplayer online games based on anchor points and path reuse

In order to solve the low performance of path finding algorithm in massive multiplayer online games,this paper proposed a path finding algorithm in Massive Multiplayer Online Games(MMOG) based on anchor points and path reuse.The algorithm reduced the unnecessary search space by using anchors and path reuse,and reduced load on server.Finally it discovered a near optimal path.The experimental results indicate that the algorithm is more efficient,and it is a practical and feasible approach to path finding in online games.

Rerouting for handoff based on the distance in wireless ATM networks

Whenever handoff for a mobile user occurs in wireless ATM network, its connection must be reestablished in the new area. This paper proposes a new path rerouting scheme based on the incremental reestablishment approach. It decides the crossover node by comparing the distances between each node in the existing path and the new location, while traversing the path backward. This scheme allows us to efficiently decide a new path whose length is close to the shortest path. In order to realistically evaluate and compare the proposed scheme, we model the distance a mobile user travels based on move speed and call duration statistics and propose a new approach for generating realistic random network. Comprehensive computer simulation for various random networks shows that the proposed scheme outperforms the previous schemes in terms of path efficiency and handoff delay. We also obtain path reuse efficiency of higher than 80%. The proposed scheme can be implemented using the information in the routing table of the underlying network.

A Model for Enhancing Connection Rerouting in Mobile Networks

In active networks (ANs) programs can be injected into routers and switches to extend the functionalities of the network. This allows programmers to enhance existing protocols and enables the rapid deployment of new protocols. The main objective of this paper is to show why ANs are ideal in solving the problem of connection rerouting and how current end-to-end based approaches can be enhanced. In this paper we propose a new model called active connection rerouting (ACR). In the ACR model, programs are dynamically injected into switches/routers in mobile networks to faciliate efficient connection rerouting during mobile host (MH) migration. We show how connection rerouting can be performed efficiently within the network. The ACR model uses a two stage optimization process: (i) path extension and (ii) lazy optimization. Unlike previous work on two stage connection rerouting ACR has the following properties: elimination of loops within switches/routers and incremental optimization which minimizes buffer requirements and maximized path reuse. ACR performs well in all topologies. Our experimental results show that ACR is efficient and scalable and it performs well in all topologies.