In this paper, we propose a model-free volumetric Next Best View (NBV) algorithm for accurate 3D reconstruction using a Markov Chain Monte Carlo method for high-mix-low-volume objects in manufacturing. The volumetric information gain based Next Best View algorithm can in real-time select the next optimal view that reveals the maximum uncertainty of the scanning environment with respect to a partially reconstructed 3D Occupancy map, without any priori knowledge of the target. Traditional Occupancy grid maps make two independence assumptions for computational tractability but suffer from the overconfident estimation of the occupancy probability for each voxel leading to less precise surface reconstructions. This paper proposes a special case of the Markov Chain Monte Carlo (MCMC) method, the Gibbs sampler, to accurately estimate the posterior occupancy probability of a voxel by randomly sampling from its high-dimensional full posterior occupancy probability given the entire volumetric map with respect to the forward sensor model with a Gaussian distribution. Numerical experiments validate the performance of the MCMC Gibbs sampler algorithm under the ROS-Industry framework to prove the accuracy of the reconstructed Occupancy map and the completeness of the registered point cloud. The proposed MCMC Occupancy mapping could be used to optimise the tuning parameters of the online NBV algorithms via the inverse sensor model to realise industry automation.INDEX TERMS Active vision, Markov chain Monte Carlo, occupancy mapping, 3D reconstruction, viewpoint planning.
Marine actinomycetes produce a substantial number of natural products with cytotoxic activity. Actinomycete strains have been isolated from sources including fishes, coral, sponges, seaweeds, mangroves and sediments. These cytotoxic compounds can be broadly categorized into four classes: polyketides; non-ribosomal peptides and hybrids; isoprenoids and hybrids; and others, among which the majority are polyketides (146 of 254). Twenty-two of the 254 compounds show potent cytotoxicity, with IC50 values at the ng/mL or nM level. This review highlights the sources, structures and antitumor activity of 254 natural products isolated from marine actinomycetes and first reported between 1989 and 2020.
Besides their decorative purposes, vehicle manufacturer logos can provide rich information for vehicle verification and classification in many applications such as security and information retrieval. However, unlike the license plate, which is designed for identification purposes, vehicle manufacturer logos are mainly designed for decorative purposes such that they might lack discriminative features themselves. Moreover, in practical applications, the vehicle manufacturer logos captured by a fixed camera vary in size. For these reasons, detection and recognition of vehicle manufacturer logos are very challenging but crucial problems to tackle. In this paper, based on preparatory works on logo localization and image segmentation, we propose a size-self-adaptive method to recognize vehicle manufacturer logos based on feature extraction and support vector machine (SVM) classifier. The experimental results demonstrate that the proposed method is more effective and robust in dealing with the recognition problem of vehicle logos in different sizes. Moreover, it has a good performance both in preciseness and speed.
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