Visual place recognition (VPR) -the act of recognizing a familiar visual place -becomes difficult when there is extreme environmental appearance change or viewpoint change. Particularly challenging is the scenario where both phenomena occur simultaneously, such as when returning for the first time along a road at night that was previously traversed during the day in the opposite direction. While such problems can be solved with panoramic sensors, humans solve this problem regularly with limited field of view vision and without needing to constantly turn around. In this paper, we present a new depth-and temporal-aware visual place recognition system that solves the opposing viewpoint, extreme appearance-change visual place recognition problem. Our system performs sequence-to-single matching by extracting depth-filtered keypoints using a stateof-the-art depth estimation pipeline, constructing a keypoint sequence over multiple frames from the reference dataset, and comparing those keypoints to those in a single query image. We evaluate the system on a challenging benchmark dataset and show that it consistently outperforms state-of-theart techniques. We also develop a range of diagnostic simulation experiments that characterize the contribution of depth-filtered keypoint sequences with respect to key domain parameters including degree of appearance change and camera motion.

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Metal Matrix Nanocomposites are made from conventional materials and alloys as matrix materials and had become prominent in improving the mechanical behaviour. In this paper, the authors have fabricated a Tin Babbitt particulate metal matrix nanocomposite reinforced with Ilmenite (FeTiO3). For systematic understanding or effect of processing parameters on the tensile behaviour, the central composite design of response surface methodology was used. Metal matrix nanocomposite was fabricated by using ultrasonic assisted stir casting technique. Stirring time, ultrasonic processing time, Wt.% of nanoparticles were taken as processing parameters. The objective of the work is to improve the tensile behaviour of Tin Babbitt and understand the effect of processing parameters on the tensile strength of the Tin Babbitt metal matrix nanocomposite and then optimise it for maximum tensile strength. It was found that tensile strength was improved due to the nano reinforcement.