| 1. |
- Mohamed, Sherif A. S., et al.
(författare)
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Monocular visual odometry based on hybrid parameterization
- 2020
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Ingår i: Proceedings of SPIE - The International Society for Optical Engineering. - : SPIE.
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Konferensbidrag (refereegranskat)abstract
- Visual odometry (VO) is one of the most challenging techniques in computer vision for autonomous vehicle/vessels. In VO, the camera pose that also represents the robot pose in ego-motion is estimated analyzing the features and pixels extracted from the camera images. Different VO techniques mainly provide different trade-offs among the resources that are being considered for odometry, such as camera resolution, computation/communication capacity, power/energy consumption, and accuracy. In this paper, a hybrid technique is proposed for camera pose estimation by combining odometry based on triangulation using the long-term period of direct-based odometry and the short-term period of inverse depth mapping. Experimental results based on the EuRoC data set shows that the proposed technique significantly outperforms the traditional direct-based pose estimation method for Micro Aerial Vehicle (MAV), keeping its potential negative effect on performance negligible.
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| 2. |
- Mohamed, Sherif A. S., et al.
(författare)
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Towards Real-Time Edge Detection for Event Cameras Based on Lifetime and Dynamic Slicing
- 2020
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Ingår i: Advances in intelligent systems and computing. - Cham : Springer. ; , s. 584-593
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Konferensbidrag (refereegranskat)abstract
- Retinal cameras, such as dynamic vision sensors (DVF), transmit asynchronous events with ultra-low latency only at significant luminance changes, unlike traditional CMOS cameras which transmit the absolute brightness of all pixels including redundant backgrounds. Due to these significant characteristics, they offer great potential to obtain efficient localization of high-speed and agile platforms. Moreover, event cameras have a high dynamic range which makes them suitable for platforms that operate indoors in low-lighting scenarios and in outdoor environments, where the camera might be pointing at a strong light source, e.g. the sun. In this paper, we propose an algorithm to detect edges in event streams coming from retinal cameras. To do that, an algorithm is developed to extract edges from events by augmenting a batch of events with their lifetimes. The lifetime of each event is computed using a local plane fitting technique. We use a batching technique to increase the frame rate of generated images since events with a high sample rate cause the processing of a single event to be computationally expensive. The size of the batch will be adjusted based on the mean optical flow of the previously generated batch. The obtained experimental results show that our proposed technique can significantly reduce the response time with the same sharpness in generating the edges.
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| 3. |
- Yasin, Jawad N., et al.
(författare)
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Night vision obstacle detection and avoidance based on Bio-Inspired Vision Sensors
- 2020
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Ingår i: Proceedings 2020 IEEE SENSORS. - : Institute of Electrical and Electronics Engineers (IEEE).
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Konferensbidrag (refereegranskat)abstract
- Moving towards autonomy, unmanned vehicles rely heavily on state-of-the-art collision avoidance systems (CAS). However, the detection of obstacles especially during night-time is still a challenging task since the lighting conditions are not sufficient for traditional cameras to function properly. Therefore, we exploit the powerful attributes of event-based cameras to perform obstacle detection in low lighting conditions. Event cameras trigger events asynchronously at high output temporal rate with high dynamic range of up to 120 dB. The algorithm filters background activity noise and extracts objects using robust Hough transform technique. The depth of each detected object is computed by triangulating 2D features extracted utilising LC-Harris. Finally, asynchronous adaptive collision avoidance (AACA) algorithm is applied for effective avoidance. Qualitative evaluation is compared using event-camera and traditional camera.
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| 4. |
- Yasin, Jawad N., et al.
(författare)
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Unmanned Aerial Vehicles (UAVs) : Collision Avoidance Systems and Approaches
- 2020
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Ingår i: IEEE Access. - : Institute of Electrical and Electronics Engineers (IEEE). - 2169-3536. ; 8, s. 105139-105155
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Tidskriftsartikel (refereegranskat)abstract
- Moving towards autonomy, unmanned vehicles rely heavily on state-of-the-art collision avoidance systems (CAS). A lot of work is being done to make the CAS as safe and reliable as possible, necessitating a comparative study of the recent work in this important area. The paper provides a comprehensive review of collision avoidance strategies used for unmanned vehicles, with the main emphasis on unmanned aerial vehicles (UAV). It is an in-depth survey of different collision avoidance techniques that are categorically explained along with a comparative analysis of the considered approaches w.r.t. different scenarios and technical aspects. This also includes a discussion on the use of different types of sensors for collision avoidance in the context of UAVs.
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