Simple fish-eye calibration method with accuracy evaluation

In this paper, a simple fish-eye radial distortion calibration procedure is described. This method avoids costly minimisation and optimisation algorithms, and is based on trivial concentricity of three extracted points. The results show that this simplicity is at the expense of increased deviation of results (and thus increased error). However, this deviation can be reduced significantly by the use of simple averaging, such that it is only marginally greater than the current state-of-the-art

Nanoflow Separation of Amino Acids for the Analysis of Cosmic Dust

The delivery of amino acids to the early Earth by interplanetary dust particles, comets, and carbonaceous meteorites could have been a significant source of the early Earth's prebiotic organic inventory. Amino acids are central to modern terrestrial biochemistry as major components of proteins and enzymes and were probably vital in the origin of life. A variety of amino acids have been detected in the CM carbonaceous meteorite Murchison, many of which are exceptionally rare in the terrestrial biosphere including a-aminoisobutyric acid (AIB) and isovaline. AIB has also been detected in a small percentage of Antarctic micrometeorite grains believed to be related to the CM meteorites We report on progress in optimizing a nanoflow liquid chromatography separation system with dual detection via laser-induced-fluorescence time of flight mass spectrometry (nLC-LIF/ToF-MS) for the analysis of o-phthaldialdehydelN-acetyl-L-cysteine (OPA/NAC) labeled amino acids in cosmic dust grains. The very low flow rates (0.1 ml/min) combined with 4 orders of magnitude lower than traditional GC-MS techniques), and specificity (compounds identities are determined by both retention time and exact mass) makes this a compelling technique. However, the development of an analytical method to achieve separation of compounds as structurally similar as amino acid monomers and produce the sharp peaks required for maximum sensitivity is challenging

E-Scooter Rider Detection and Classification in Dense Urban Environments

Accurate detection and classification of vulnerable road users is a safety critical requirement for the deployment of autonomous vehicles in heterogeneous traffic. Although similar in physical appearance to pedestrians, e-scooter riders follow distinctly different characteristics of movement and can reach speeds of up to 45kmph. The challenge of detecting e-scooter riders is exacerbated in urban environments where the frequency of partial occlusion is increased as riders navigate between vehicles, traffic infrastructure and other road users. This can lead to the non-detection or mis-classification of e-scooter riders as pedestrians, providing inaccurate information for accident mitigation and path planning in autonomous vehicle applications. This research introduces a novel benchmark for partially occluded e-scooter rider detection to facilitate the objective characterization of detection models. A novel, occlusion-aware method of e-scooter rider detection is presented that achieves a 15.93% improvement in detection performance over the current state of the art

The Impact of Partial Occlusion on Pedestrian Detectability

Robust detection of vulnerable road users is a safety critical requirement for the deployment of autonomous vehicles in heterogeneous traffic. One of the most complex outstanding challenges is that of partial occlusion where a target object is only partially available to the sensor due to obstruction by another foreground object. A number of leading pedestrian detection benchmarks provide annotation for partial occlusion, however each benchmark varies greatly in their definition of the occurrence and severity of occlusion. Recent research demonstrates that a high degree of subjectivity is used to classify occlusion level in these cases and occlusion is typically categorized into 2 to 3 broad categories such as partially and heavily occluded. This can lead to inaccurate or inconsistent reporting of pedestrian detection model performance depending on which benchmark is used. This research introduces a novel, objective benchmark for partially occluded pedestrian detection to facilitate the objective characterization of pedestrian detection models. Characterization is carried out on seven popular pedestrian detection models for a range of occlusion levels from 0-99%, in order to demonstrate the efficacy and increased analysis capabilities of the proposed characterization method. Results demonstrate that pedestrian detection performance degrades, and the number of false negative detections increase as pedestrian occlusion level increases. Of the seven popular pedestrian detection routines characterized, CenterNet has the greatest overall performance, followed by SSDlite. RetinaNet has the lowest overall detection performance across the range of occlusion levels

Revisiting Modality Imbalance In Multimodal Pedestrian Detection

Multimodal learning, particularly for pedestrian detection, has recently received emphasis due to its capability to function equally well in several critical autonomous driving scenarios such as low-light, night-time, and adverse weather conditions. However, in most cases, the training distribution largely emphasizes the contribution of one specific input that makes the network biased towards one modality. Hence, the generalization of such models becomes a significant problem where the non-dominant input modality during training could be contributing more to the course of inference. Here, we introduce a novel training setup with regularizer in the multimodal architecture to resolve the problem of this disparity between the modalities. Specifically, our regularizer term helps to make the feature fusion method more robust by considering both the feature extractors equivalently important during the training to extract the multimodal distribution which is referred to as removing the imbalance problem. Furthermore, our decoupling concept of output stream helps the detection task by sharing the spatial sensitive information mutually. Extensive experiments of the proposed method on KAIST and UTokyo datasets shows improvement of the respective state-of-the-art performance.Comment: 5 pages, 3 figure, 4 table

A Propensity for n-omega-Amino Acids in Thermally-Altered Antarctic Meteorites

Carbonaceous meteorites are known to contain a wealth of indigenous organic molecules, including amino acids, which suggests that these meteorites could have been an important source of prebiotic organic material during the origins of life on Earth and possibly elsewhere. We report the detection of extraterrestrial amino acids in thermally-altered type 3 CV and CO carbonaceous chondrites and ureilites recovered from Antarctica. The amino acid concentrations of the thirteen Antarctic meteorites were generally less abundant than in more amino acid-rich CI, CM, and CR carbonaceous chondrites that experienced much lower temperature aqueous alteration on their parent bodies. In contrast to low-temperature aqueously-altered meteorites that show complete structural diversity in amino acids formed predominantly by Strecker-cyanohydrin synthesis, the thermally-altered meteorites studied here are dominated by small, straight-chain, amine terminal (n-omega-amino) amino acids that are not consistent with Strecker formation. The carbon isotopic ratios of two extraterrestrial n-omega-amino acids measured in one of the CV chondrites are consistent with C-13-depletions observed previously in hydrocarbons produced by Fischer-Tropsch type reactions. The predominance of n-omega-amino acid isomers in thermally-altered meteorites hints at cosmochemical mechanisms for the preferential formation and preservation of a small subset of the possible amino acids

Detecting Organic Compounds Released from Iron Oxidizing Bacteria using Sample Analysis at Mars (SAM) Like Instrument Protocols

Mars is a planet of great interest for Astrobiology since its past environmental conditions are thought to have been favourable for the emergence life. At present, the Red Planet is extremely cold and dry and the surface is exposed to intense UV and ionizing radiation, conditions generally considered to be incompatible with life as we know it on Earth. It was proposed that the shallow subsurface of Mars, where temperatures can be above freezing and liquid water can exist on rock surfaces, could harbor chemolithoautotrophic bacteria such as the iron oxidizing microorganism Pseudomonas sp. HerB. The Mars Science Laboratory (MSL) mission will provide the next opportunity to carry out in situ measurements for organic compounds of possible biological origin on Mars. One instrument onboard MSL, called the Sample Analysis at Mars (SAM) instrument suite, will carry out a broad and sensitive search for organic compounds in surface samples using either high temperature pyrolysis or chemical extraction followed by gas chromatography mass spectrometry. We present gas chromatograph mass spectrometer (GC/MS) data on crushed olivine rock powders that have been inoculated with Pseudomonas sp. HerB at different concentrations ranging from approx 10(exp 2) to 10(exp 7) cells per gram. The inoculated olivine samples were heated under helium carrier gas flow at 500 C and the pyrolysis products concentrated using a SAM-like hydrocarbon trap set at -20 C followed by trap heating and analysis by GC/Ms. In addition, the samples were also extracted using a low temperature "one-pot" chemical extraction technique using N-methyl, N-(tert-butyldimethylsilyl) trifluoroacetamide (MTBSTFA) as the silylating agent prior to GC/MS analysis. We identified several aldehydes, thiols, and alkene nitriles after pyrolysis GC/MS analysis of the bacteria that were not found in the olivine control samples that had not been inoculated with bacteria. The distribution of pyrolysis products extracted from the bacteria was clearly distinct from similar GC/MS analyses of the carbonaceous meteorite Murchison that was dominated by sulfur containing aromatic compounds. A similar comparison, if organic compounds are detected by SAM on Mars, could be useful to help discriminate between meteoritic or biological origins

Time--delay autosynchronization of the spatio-temporal dynamics in resonant tunneling diodes

The double barrier resonant tunneling diode exhibits complex spatio-temporal patterns including low-dimensional chaos when operated in an active external circuit. We demonstrate how autosynchronization by time--delayed feedback control can be used to select and stabilize specific current density patterns in a noninvasive way. We compare the efficiency of different control schemes involving feedback in either local spatial or global degrees of freedom. The numerically obtained Floquet exponents are explained by analytical results from linear stability analysis.Comment: 10 pages, 16 figure