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"Motion detectors"
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Eye pupil signals life motion perception
The ability to readily detect and recognize biological motion (BM) is fundamental to survival and interpersonal communication. However, perception of BM is strongly disrupted when it is shown upside down. This well-known inversion effect is proposed to be caused by a life motion detection mechanism highly tuned to gravity-compatible motion cues. In the current study, we assessed the inversion effect in BM perception using a no-report pupillometry. We found that the pupil size was significantly enlarged when observers viewed upright BMs (gravity-compatible) compared with the inverted counterparts (gravity-incompatible). Importantly, such an effect critically depended on the dynamic biological characteristics, and could be extended to local feet motion signals. These findings demonstrate that the eye pupil can signal gravity-dependent life motion perception. More importantly, with the convenience, objectivity, and noninvasiveness of pupillometry, the current study paves the way for the potential application of pupillary responses in detecting the deficiency of life motion perception in individuals with socio-cognitive disorders.
Journal Article
Life motion signals modulate visual working memory
Previous research has demonstrated that biological motion (BM) cues can induce a reflexive attentional orienting effect, a phenomenon referred to as
social attention
. However, it remains undetermined whether BM cues can further affect higher-order cognitive processes, such as visual working memory (WM). By combining a modified central pre-cueing paradigm with a traditional WM change detection task, the current study investigated whether the walking direction of BM, as a non-predictive central cue, could modulate the encoding process of WM. Results revealed a significant improvement in WM performance for the items appearing at the location cued by the walking direction of BM. The observed effect disappeared when the BM cues were shown inverted, or when the critical biological characteristics of the cues were removed. Crucially, this effect could be extended to upright feet motion cues without global configuration, reflecting the key role of local BM signals in modulating WM. More importantly, such a BM-induced modulation effect was not observed with inanimate motion cues, although these cues can also elicit attentional effects. Our findings suggest that the attentional effect induced by life motion signals can penetrate to higher-order cognitive processes, and provide compelling evidence for the existence of “life motion detector” in the human brain from a high-level cognitive function perspective.
Journal Article
A Smart Sensing System of Water Quality and Intake Monitoring for Livestock and Wild Animals
This paper presents a water intake monitoring system for animal agriculture that tracks individual animal watering behavior, water quality, and water consumption. The system is deployed in an outdoor environment to reach remote areas. The proposed system integrates motion detectors, cameras, water level sensors, flow meters, Radio-Frequency Identification (RFID) systems, and water temperature sensors. The data collection and control are performed using Arduino microcontrollers with custom-designed circuit boards. The data associated with each drinking event are water consumption, water temperature, drinking duration, animal identification, and pictures. The data and pictures are automatically stored on Secure Digital (SD) cards. The prototypes are deployed in a remote grazing site located in Tucumcari, New Mexico, USA. The system can be used to perform water consumption and watering behavior studies of both domestic animals and wild animals. The current system automatically records the drinking behavior of 29 cows in a two-week duration in the remote ranch.
Journal Article
Temporal Noise Reduction Algorithm with an Adaptive Threshold for Cooled Thermal Imaging Optoelectronic Systems
The results of the development of a recursive algorithm for temporal noise reduction with an adaptive threshold for thermal imaging systems are presented. This algorithm is designed to reduce the level of temporal noise based on the results of analyzing a sequence of images obtained using a thermal imaging channel. A mathematical model of the algorithm is provided, as well as the required amount of computing resources needed for its hardware implementation in field programmable gate arrays (FPGAs). Several characteristics of the thermal imaging system with the developed algorithm were measured and conclusions were made about the positive influence of the algorithm on its noise equivalent temperature difference (NETD).
Journal Article
Motion Detectors as Additional Monitoring Devices in the Intensive Care Unit—A Proof-of-Concept Study
Background: Monitoring the vital signs of delirious patients in an intensive care unit (ICU) is challenging, as they might (un-)intentionally remove devices attached to their bodies. In mock-up scenarios, we systematically assessed whether a motion detector (MD) attached to the bed may help in identifying emergencies. Methods: We recruited 15 employees of the ICU and equipped an ICU bed with an MD (IRON Software GmbH, Grünwald, Germany). Participants were asked to replay 22 mock-up scenes of one-minute duration each: 12 scenes with movements and 10 without movements, of which 5 were emergency scenes (“lying dead-still, with no or very shallow breathing”). Blinded recordings were presented to an evaluation panel consisting of an experienced ICU nurse and a physician, who was asked to assess and rate the presence of motions. Results: Fifteen participants (nine women; 173 ± 7.0 cm; 78 ± 19 kg) joined the study. In total, 286 out of 330 scenes (86.7%) were rated correctly. Ratings were false negative (FN: “no movements detected, but recorded”) in 7 out of 180 motion scenes (3.9%). Ratings were false positive (FP: “movements detected, but not recorded”) in 37 out of 150 scenes (24.7%), more often in men than women (26 out of 60 vs. 11 out of 90, respectively; p < 0.001). Of note, in 16 of these 37 FP-rated scenes, a vibrating mobile phone was identified as a potential confounder. The emergency scenes were correctly rated in 64 of the 75 runs (85.3%); 10 of the 11 FP-rated scenes occurred in male subjects. Conclusions: The MD allowed for identifying motions of test subjects with high sensitivity (96%) and acceptable specificity (75%). Accuracy might increase further if activities are recorded continuously under real-world conditions.
Journal Article
THE DESIGN OF A TESTING DEVICE FOR PASSIVE INFRARED MOTION DETECTORS
As part of research and development work at the Department of Security management of the University of Zilina, we concerned ourselves with testing various types of motion detectors. Testing of detectors in general serves to acquire a basis of data for software developed at the Faculty, which serve to measure and evaluate the levels of physical security of an object. Detectors are tested at the faculty in terms of reliability and breach resilience. We are mostly interested in the time it takes to detect an intruder. Until now, we have not tested several detectors at once. Testing of a larger pool of detectors at the same time is useful when comparing their detection capabilities and when testing the ability of the alarm system control unit and its load capacity. The article contains a concept, design, blueprint and principle of operation of a testing device, designed to test a greater number of passive infrared motion detectors at one, works. The designed testing device allows for testing the detection ability of several motion detectors at once, compare the time it takes them to disconnect their NC contacts and also compare the reaction times of individual motion detectors. The article also contains a description of the device’s structure and recording of the acquired results which is based on a free Arduino platform and their usability in practice. The proposed device will be further improved as part of our R&D activities.
Journal Article
Robust motion detection and classification in real-life scenarios using motion vectors
In dynamic settings such as security, autonomous driving, and robotics, effective motion detection and classification are crucial for accurate tracking amidst target and background movements. Traditional approaches, typically designed for static environments, face challenges in complex scenes with multiple types of motion. This research presents a robust algorithm for motion detection in fully dynamic scenarios, utilizing the macro block technique to generate motion vectors, followed by motion vector analysis to classify distinct types of motion. These include camera motion, object motion, background motion, and complex motion, where both background and foreground move simultaneously. By segmenting and categorizing these motion types, the proposed approach improves detection precision in cluttered, real-world environments. Furthermore, the algorithm adapts to lighting variations and is independent of specific sensor setups. Moreover, the high agreement with human judgment, achieving a 90% accuracy rate, underscores the model’s robustness and potential applicability in real-world scenarios where dynamic backgrounds are prevalent. This establishes a framework for future research in dynamic motion detection and classification.
Journal Article
A survey of depth and inertial sensor fusion for human action recognition
A number of review or survey articles have previously appeared on human action recognition where either vision sensors or inertial sensors are used individually. Considering that each sensor modality has its own limitations, in a number of previously published papers, it has been shown that the fusion of vision and inertial sensor data improves the accuracy of recognition. This survey article provides an overview of the recent investigations where both vision and inertial sensors are used together and simultaneously to perform human action recognition more effectively. The thrust of this survey is on the utilization of depth cameras and inertial sensors as these two types of sensors are cost-effective, commercially available, and more significantly they both provide 3D human action data. An overview of the components necessary to achieve fusion of data from depth and inertial sensors is provided. In addition, a review of the publicly available datasets that include depth and inertial data which are simultaneously captured via depth and inertial sensors is presented.
Journal Article
Finding the gap: neuromorphic motion-vision in dense environments
Animals have evolved mechanisms to travel safely and efficiently within different habitats. On a journey in dense terrains animals avoid collisions and cross narrow passages while controlling an overall course. Multiple hypotheses target how animals solve challenges faced during such travel. Here we show that a single mechanism enables safe and efficient travel. We developed a robot inspired by insects. It has remarkable capabilities to travel in dense terrain, avoiding collisions, crossing gaps and selecting safe passages. These capabilities are accomplished by a neuromorphic network steering the robot toward regions of low apparent motion. Our system leverages knowledge about vision processing and obstacle avoidance in insects. Our results demonstrate how insects might safely travel through diverse habitats. We anticipate our system to be a working hypothesis to study insects’ travels in dense terrains. Furthermore, it illustrates that we can design novel hardware systems by understanding the underlying mechanisms driving behaviour.
Inspired by insects in nature, the authors develop a neuromorphic robotic system with obstacle avoidance, tunnel centering and gap crossing capabilities. Their robotic system accomplishes these multiple capabilities by steering towards regions of low apparent motion.
Journal Article