2 edition of Real-time occupant detection in high dynamic range environments found in the catalog.
Real-time occupant detection in high dynamic range environments
|LC Classifications||TK8316 .K63 2004|
|The Physical Object|
|Pagination||xxiv, 171 p. :|
|Number of Pages||171|
|LC Control Number||2007476959|
Occupant Classification System for Automotive Airbag Suppression need for a low-cost, high reliability embedded real-time airbag suppression system. Additional testing and may have considerable dynamic range due to the simultaneous existence of shadows near the occupant’s legs and bright patches due to direct sunlight on the head. In general, a detector fulfils the condition of linearity (see § III) only for a limited range of the input signal level. There are two effects which define the boundaries of this dynamic range: • At very low levels of the input signal, the detector's output is largely dominated by noise.
The Signal-to-Noise Ratio (SNR) and Dynamic Range (DR) are two common parameters used to specify the electrical performance of a spectrometer. This technical note will describe how they are defined and how to measure and calculate them. The signal out of the spectrometer is a digital signal between 0 and 2ⁿ -1, where n is the number of bits in the Analogue-to-Digital (A/D) converter on the. Real-time PCR detection of rbcL target nucleic acid has proven to be extremely sensitive; in addition, a large dynamic range with a quantitative detection limit of approximately 1, gene copies has been observed. The assay is linear through at least 6 orders of magnitude covering the entire range of traditional probing assays while being.
Such a programmable camera would even provide the possibility to create true high dynamic range images, if the response function could be determined for the integrated camera. However, to the best of our knowledge, the only mobile device capable of controlling camera parameters is the Nokia N with Frankencam API . An occupancy sensor is an indoor motion detecting device used to detect the presence of a person to automatically control lights or temperature or ventilation systems. The sensors use infrared, ultrasonic, microwave, or other term encompasses devices as different as PIR sensors, hotel room keycard locks and smart ncy sensors are typically used to save energy.
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Real-time occupant detection system in an active illumination environment by large intensity fluctuations and hence a high optical dynamic range (HDR). in high dynamic range environments. Real-time occupant classification in high dynamic range environments Conference Paper (PDF Available) July with 47 Reads How we measure 'reads'.
Real-time occupant detection in high dynamic range environments Author: Koch, Carsten. ISNI: Awarding Body: City University Current Institution: City, University of London Date of Award: Availability of Full Text: Full text unavailable from EThOS.
Real-time occupant detection in high dynamic range environments. By Carsten Koch. Abstract. EThOS - Electronic Theses Online ServiceGBUnited Kingdo Topics: - Mechanical, industrial, civil and marine engineering, general.
Year: OAI identifier: Author: Carsten Koch. Real-time occupant detection system in an active illumination environment J.J. Yoon and T.J. Ellis1 City University, London, EC1V OHB, UK 1Kingston University, Surrey, KT1 2EE, UK Abstract A single grey-scale camera based object classiﬁcation system for vehicle airbag deployment control in wide and frequent illumination variations is introduced.
Occupancy Detection at Smart Home Using Real-Time Dynamic Thresholding of Flexiforce Sensor Abstract: Monitoring of the activities of the occupant is paramount important in the field of ambient-assisted living environment.
Sensors are widely used to collect, store, and analyze on the continuous stream of data of the observation of their day-to. The algorithms are systematically evaluated through extensive real-time occupant tests.
in high dynamic range environments. for real-time obstacle detection in front of a moving car using. Some examples include occupant detection and classification , , , out of position detection (OOP), automatic head rest control (HRC), personalization, driver monitoring  (drowsiness.
In this paper, an embedded photometric device is proposed to combine high dynamic range (HDR) imaging based high-resolution sky luminance monitoring with quasi real-time on-board daylighting computing, composed of a low-cost image sensor and a field.
For real-time performance of the full ML pipeline consisting of pose detection and tracking models, each component must be very fast, using only a few milliseconds per frame. To accomplish this, we observe that the strongest signal to the neural network about the position of the torso is the person's face (due to its high-contrast features and.
The proposed IoT-based occupancy detection system is composed of three steps: (a) data collection, (2) data processing and storing, and (3) data visualization and analysis, as illustrated in Fig.
detect occupancy from the collected sensor data in the first step, the system uses the proposed occupancy detection method in the second step. Non-vision sensors have been used for the tasks of occupant detection [19, 33] and classification , but there are a number of incentives to replace these with a camera based include the possibility of introducing additional functionality without any additional hardware (for example, determining if an occupant is using a control surface ), and reducing the cost to the.
Occupant detection, as opposed to occupant counting. Occupant detection within a semi-open space (an ofﬁce cubicle). The use of multiple low-cost sensor types to improve the detection quality over a single sensor alone.
The use of Decision Trees to automatically select the features with the highest information gain and exploit. This study presents a new daylight glare control framework, using a low-cost, window-mounted programmable High Dynamic Range Image (HDRI) sensor with a wide fisheye lens.
With proper calibration, the sensor can accurately measure the luminance, size, and relative position of any exterior glare sources in real time, using per pixel analysis.
Because depth background subtraction is applied, occupant detection works well, contrary to the conventional CCD camera that only works well in a high illumination environment.
As shown in Fig. 8 (f), when lighting conditions are unstable due to the flickering of the fluorescent lighting, objects are in a shadow, or a shiny floor throws a. Alhakamy A., Tuceryan M. () Polarization-Based Illumination Detection for Coherent Augmented Reality Scene Rendering in Dynamic Environments.
In: Gavrilova M., Chang J., Thalmann N., Hitzer E., Ishikawa H. (eds) Advances in Computer Graphics. CGI Lecture Notes in Computer Science, vol Springer, Cham. First Online 12 June detection and occupant's behavioral patterns can be used to manage and control buildings more intelligently for ventilation, heating and cooling, and energy e ﬃ ciency [ 1, 2 ].
Abstract: Static occupant classification is an important requirement in designing so-called "smart airbags." Systems for this purpose can be either based on pressure sensors or vision sensors.
Vision-based systems are advantageous over pressure-sensor-based systems as they can provide additional functionalities like dynamic occupant-position analysis or child-seat orientation detection.
A real-time PCR assay was developed for detecting the presence of Acinetobacter baumannii on hospital equipment and compared to conventional bacterial culture using hospital environmental samples.
The real-time PCR detected contaminated surfaces in 4 h with high sensitivity (%) compared to conventional culture. Abstract: Acquiring High Dynamic Range (HDR) light-fields from several images with different exposures (sensor integration periods) has been widely considered for static camera positions.
In this paper a new approach is proposed that enables 3D HDR environment maps to be acquired directly from a dynamic set of images in real-time. Real-time PCR is characterized by high sensitivity, excellent precision and large dynamic range, and has become the method of choice for quantitative gene expression measurements.
For accurate gene expression profiling by real-time PCR, several parameters must be considered and carefully validated.Dynamic range (abbreviated DR, DNR, or DYR) is the ratio between the largest and smallest values that a certain quantity can assume. It is often used in the context of signals, like sound and is measured either as a ratio or as a base or base-2 (doublings, bits or stops) logarithmic value of the difference between the smallest and largest signal values.This is the main resources page for the book Real-Time Rendering, Fourth Edition, by Tomas Akenine-Möller, Eric Haines, Naty Hoffman, Angelo Pesce, Michał Iwanicki, and Sébastien Hillaire, pages, from A K Peters/CRC Press, ISBNISBNlist price $ (Amazon $, Look inside; Kindle $