scholarly journals Insects and associated arthropods analyzed during medicolegal death investigations in Harris County, Texas, USA: January 2013-April 2016

2016 ◽  
Author(s):  
Michelle R. Sanford
Keyword(s):  
Forensic Entomology ◽  
Gulf Coast ◽  
Forensic Sciences ◽  
Full Time ◽  
Harris County ◽  
Species List ◽  
Manner Of Death ◽  
Outdoor Scenes ◽  
Indoor Scenes ◽  
Indoor And Outdoor

ABSTRACTThe application of insect and arthropod information to medicolegal death investigations is one of the more exacting applications of entomology. Historically limited to homicide investigations, the integration of full time forensic entomology services to the medical examiner’s office in Harris County has opened up the opportunity to apply entomology to a wide variety of manner of death classifications and types of scenes to make observations on a number of different geographical and species-level trends in Harris County, Texas, USA. In this study, a retrospective analysis was made of 203 forensic entomology cases analyzed during the course of medicolegal death investigations performed by the Harris County Institute of Forensic Sciences in Houston, TX, USA from January 2013 through April 2016. These cases included all manner of death classifications, stages of decomposition and a variety of different scene types that were classified into decedents transported from the hospital (typically associated with myiasis or sting allergy; 3.0%), outdoor scenes (32.0%) or indoor scenes (65.0%). Ambient scene air temperature at the time scene investigation was the only significantly different factor observed between indoor and outdoor scenes with average indoor scene temperature being slightly cooler (25.2°C) than that observed outdoors (28.0°C). Relative humidity was not found to be significantly different between scene types. Most of the indoor scenes were classified as natural (43.3%) whereas most of the outdoor scenes were classified as homicides (12.3%). All other manner of death classifications came from both indoor and outdoor scenes. Several species were found to be significantly associated with indoor scenes as indicated by a binomial test, including Blaesoxipha plinthopyga (Sarcophagidae), all Sarcophagidae including B. plinthopyga, Megaselia scalaris (Phoridae), Synthesiomyia nudiseta (Muscidae) and Lucilia cuprina (Calliphoridae). The only species that was a significant indicator of an outdoor scene was Lucilia eximia (Calliphoridae). All other insect species that were collected in five or more cases were collected from both indoor and outdoor scenes. A species list with month of collection and basic scene characteristics with the length of the estimated time of colonization is also presented. The data presented here provide valuable casework related species data for Harris County, TX and nearby areas on the Gulf Coast that can be used to compare to other climate regions with other species assemblages and to assist in identifying new species introductions to the area. This study also highlights the importance of potential sources of uncertainty in preparation and interpretation of forensic entomology reports from different scene types.

scholarly journals Fusing Multimodal Video Data for Detecting Moving Objects/Targets in Challenging Indoor and Outdoor Scenes

2019 ◽  
Vol 11 (4) ◽  
pp. 446 ◽  
Author(s):  
Zacharias Kandylakis ◽  
Konstantinos Vasili ◽  
Konstantinos Karantzalos
Keyword(s):  
Object Detection ◽  
Moving Objects ◽  
Local Coordinate System ◽  
Image Plane ◽  
Hyperspectral Data ◽  
Video Data ◽  
Outdoor Scenes ◽  
Indoor Scenes ◽  
Video Sensors ◽  
Indoor And Outdoor

Single sensor systems and standard optical—usually RGB CCTV video cameras—fail to provide adequate observations, or the amount of spectral information required to build rich, expressive, discriminative features for object detection and tracking tasks in challenging outdoor and indoor scenes under various environmental/illumination conditions. Towards this direction, we have designed a multisensor system based on thermal, shortwave infrared, and hyperspectral video sensors and propose a processing pipeline able to perform in real-time object detection tasks despite the huge amount of the concurrently acquired video streams. In particular, in order to avoid the computationally intensive coregistration of the hyperspectral data with other imaging modalities, the initially detected targets are projected through a local coordinate system on the hypercube image plane. Regarding the object detection, a detector-agnostic procedure has been developed, integrating both unsupervised (background subtraction) and supervised (deep learning convolutional neural networks) techniques for validation purposes. The detected and verified targets are extracted through the fusion and data association steps based on temporal spectral signatures of both target and background. The quite promising experimental results in challenging indoor and outdoor scenes indicated the robust and efficient performance of the developed methodology under different conditions like fog, smoke, and illumination changes.

THE USE OF OPTICAL FLOW FOR THE AUTONOMOUS NAVIGATION

1992 ◽  
Vol 03 (supp01) ◽  
pp. 121-137 ◽  
Author(s):  
Antonio Malisia ◽  
Andrea Baghino ◽  
Marco Campani ◽  
Marco Straforini ◽  
Vincent Torre
Keyword(s):  
Optical Flow ◽  
Autonomous Navigation ◽  
Moving Vehicle ◽  
Mobile Vehicle ◽  
Outdoor Scenes ◽  
Outdoor Environments ◽  
Indoor Scenes ◽  
Indoor And Outdoor Environments ◽  
Vision Module ◽  
Indoor And Outdoor

Insects and a lot of other animals use the optical flow to control the direction of their motion and to avoid obstacles. This paper describes experiments suggesting the possible use of the optical flow for the navigation of a robot moving in indoor and outdoor environments. In indoor scenes, such as corridors, offices and laboratories, the optical flow is used to detect and localize obstacles. These routines are based on the computation of a reduced optical flow. Almost real time performance was obtained with standard workstations, such as SUN 3 or SUN Sparcstation 1. The mobile vehicle is usually able to avoid large obstacles such as a chair or a human, but it is not able to avoid thin obstacles such as a rod or a bar. The avoidance performances of the proposed algorithm critically depend on the feedback loop between the vision module and the motor system. In outdoor scenes the optical flow can be used to understand the egomotion, that is to obtain information on the absolute velocity of the moving vehicle. The optical flow is corrected for shocks and vibration present during image acquisition. Regions of the image are extracted, where the optical flow is reliable, and the information on egomotion is recovered from the optical flow here obtained. These results suggest that the optical flow can be successfully used by biological and artificial systems for controlling their motion and for avoiding obstacles.

scholarly journals CONFIGURATION AND SIMULATION TOOL FOR 360-DEGREE STEREO CAMERA RIG

2019 ◽  
Vol XLII-2/W13 ◽  
pp. 793-798
Author(s):  
O. Hasler ◽  
B. Loesch ◽  
S. Blaser ◽  
S. Nebiker
Keyword(s):  
Focal Length ◽  
Evaluation Process ◽  
Camera System ◽  
Stereo Camera ◽  
Multiple Parameters ◽  
Outdoor Scenes ◽  
Indoor Scenes ◽  
User Friendly ◽  
Intrinsic And Extrinsic Parameters ◽  
Indoor And Outdoor

<p><strong>Abstract.</strong> The demand for capturing outdoor and indoor scenes is rising with the digitalization trend in the construction industry. An efficient solution for capturing these environments is mobile mapping. Image-based systems with 360&amp;deg; panoramic coverage allow a rapid data acquisition and can be made user-friendly accessible when hosted in a cloud-based 3D geoinformation service. The design of such a 360° stereo camera system is challenging since multiple parameters like focal length, stereo base length and environmental restrictions such as narrow corridors are influencing each other. Therefore, this paper presents a toolset, which helps configuring and evaluating such a panorama stereo camera rig. The first tool is used to determine, from which distance on 360&amp;deg; stereo coverage depending on the parametrization of the rig is achieved. The second tool can be used to capture images with the parametrized camera rig in different virtual indoor and outdoor scenes. The last tool supports stitching the captured images together in respect of the intrinsic and extrinsic parameters from the configuration tool. This toolset radically simplifies the evaluation process of a 360&amp;deg; stereo camera configuration and decreases the number of physical MMS prototypes.</p>

scholarly journals Flexible time course of spatial frequency use during scene categorization

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sandro L. Wiesmann ◽  
Laurent Caplette ◽  
Verena Willenbockel ◽  
Frédéric Gosselin ◽  
Melissa L.-H. Võ
Keyword(s):  
Time Course ◽  
Task Characteristics ◽  
Scene Categorization ◽  
Fine Grained ◽  
Spatial Frequencies ◽  
Outdoor Scenes ◽  
Indoor Scenes ◽  
Fine Pattern ◽  
Late Stages ◽  
Basic Level

AbstractHuman observers can quickly and accurately categorize scenes. This remarkable ability is related to the usage of information at different spatial frequencies (SFs) following a coarse-to-fine pattern: Low SFs, conveying coarse layout information, are thought to be used earlier than high SFs, representing more fine-grained information. Alternatives to this pattern have rarely been considered. Here, we probed all possible SF usage strategies randomly with high resolution in both the SF and time dimensions at two categorization levels. We show that correct basic-level categorizations of indoor scenes are linked to the sampling of relatively high SFs, whereas correct outdoor scene categorizations are predicted by an early use of high SFs and a later use of low SFs (fine-to-coarse pattern of SF usage). Superordinate-level categorizations (indoor vs. outdoor scenes) rely on lower SFs early on, followed by a shift to higher SFs and a subsequent shift back to lower SFs in late stages. In summary, our results show no consistent pattern of SF usage across tasks and only partially replicate the diagnostic SFs found in previous studies. We therefore propose that SF sampling strategies of observers differ with varying stimulus and task characteristics, thus favouring the notion of flexible SF usage.

Novel Scenes Improve Recollection and Recall of Words

2008 ◽  
Vol 20 (7) ◽  
pp. 1250-1265 ◽  
Author(s):  
Daniela B. Fenker ◽  
Julietta U. Frey ◽  
Hartmut Schuetze ◽  
Dorothee Heipertz ◽  
Hans-Jochen Heinze ◽  
...  
Keyword(s):  
Specific Activity ◽  
Activity Patterns ◽  
Long Term Potentiation ◽  
Contextual Memory ◽  
Memory Enhancement ◽  
Term Potentiation ◽  
Outdoor Scenes ◽  
Indoor And Outdoor ◽  
Hippocampus Dependent Memory

Exploring a novel environment can facilitate subsequent hippocampal long-term potentiation in animals. We report a related behavioral enhancement in humans. In two separate experiments, recollection and free recall, both measures of hippocampus-dependent memory formation, were enhanced for words studied after a 5-min exposure to unrelated novel as opposed to familiar images depicting indoor and outdoor scenes. With functional magnetic resonance imaging, the enhancement was predicted by specific activity patterns observed during novelty exposure in parahippocampal and dorsal prefrontal cortices, regions which are known to be linked to attentional orienting to novel stimuli and perceptual processing of scenes. Novelty was also associated with activation of the substantia nigra/ventral tegmental area of the midbrain and the hippocampus, but these activations did not correlate with contextual memory enhancement. These findings indicate remarkable parallels between contextual memory enhancement in humans and existing evidence regarding contextually enhanced hippocampal plasticity in animals. They provide specific behavioral clues to enhancing hippocampus-dependent memory in humans.

scholarly journals 3D Object Detection Using Scale Invariant and Feature Reweighting Networks

2019 ◽  
Vol 33 ◽  
pp. 9267-9274 ◽  
Author(s):  
Xin Zhao ◽  
Zhe Liu ◽  
Ruolan Hu ◽  
Kaiqi Huang
Keyword(s):  
Object Detection ◽  
Network Architecture ◽  
Point Clouds ◽  
Scale Invariant ◽  
3D Object ◽  
Outdoor Scenes ◽  
Indoor Scenes ◽  
Bounding Boxes ◽  
The One ◽  
3D Object Detection

3D object detection plays an important role in a large number of real-world applications. It requires us to estimate the localizations and the orientations of 3D objects in real scenes. In this paper, we present a new network architecture which focuses on utilizing the front view images and frustum point clouds to generate 3D detection results. On the one hand, a PointSIFT module is utilized to improve the performance of 3D segmentation. It can capture the information from different orientations in space and the robustness to different scale shapes. On the other hand, our network obtains the useful features and suppresses the features with less information by a SENet module. This module reweights channel features and estimates the 3D bounding boxes more effectively. Our method is evaluated on both KITTI dataset for outdoor scenes and SUN-RGBD dataset for indoor scenes. The experimental results illustrate that our method achieves better performance than the state-of-the-art methods especially when point clouds are highly sparse.

scholarly journals SREVAS: Shading Based Surface Refinement under Varying Albedo and Specularity

2020 ◽  
Vol 12 (21) ◽  
pp. 3488
Author(s):  
Zhihua Hu ◽  
Yaolin Hou ◽  
Pengjie Tao ◽  
Jie Shan
Keyword(s):  
Stereo Vision ◽  
Specular Reflection ◽  
Low Cost ◽  
Shape From Shading ◽  
Specular Reflectance ◽  
Specular Reflections ◽  
New Development ◽  
Outdoor Scenes ◽  
Indoor Scenes ◽  
Surface Refinement

Shape-from-shading and stereo vision are two complementary methods to reconstruct 3D surface from images. Stereo vision can reconstruct the overall shape well but is vulnerable in texture-less and non-Lambertian areas where shape-from-shading can recover fine details. This paper presents a novel, generic shading based method to refine the surface generated by multi-view stereo. Different from most of the shading based surface refinement methods, the new development does not assume the ideal Lambertian reflectance, known illumination, or uniform surface albedo. Instead, specular reflectance is taken into account while the illumination can be arbitrary and the albedo can be non-uniform. Surface refinement is achieved by solving an objective function where the imaging process is modeled with spherical harmonics illumination and specular reflectance. Our experiments are carried out using images of indoor scenes with obvious specular reflection and of outdoor scenes with a mixture of Lambertian and specular reflections. Comparing to surfaces created by current multi-view stereo and shape-from-shading methods, the developed method can recover more fine details with lower omission rates (6.11% vs. 24.25%) in the scenes evaluated. The benefit is more apparent when the images are taken with low-cost, off-the-shelf cameras. It is therefore recommended that a general shading model consisting of varying albedo and specularity shall be used in routine surface reconstruction practice.

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