Motion detection with low cost hardware for PTZ cameras

Benito-Picazo, Jesús; Domínguez, Enrique; Palomo, Esteban J.; López‐Rubio, Ezequiel; Ortiz-de-Lazcano-Lobato, Juan Miguel

doi:10.3233/ica-180579

Cited by 8 publications

(4 citation statements)

References 36 publications

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“…For i7-8700, half of the cores (6) are enough to saturate the processor. For i7-9700, the best runtime is achieved with full occupancy of the cores (8). We can see how the runtime decrease is proportional to the amount of cores again.…”

Section: Resultsmentioning

confidence: 91%

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A membrane parallel rapidly-exploring random tree algorithm for robotic motion planning

Pérez–Hurtado

Amor

Zhang

et al. 2020

ICA

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In recent years, incremental sampling-based motion planning algorithms have been widely used to solve robot motion planning problems in high-dimensional configuration spaces. In particular, the Rapidly-exploring Random Tree (RRT) algorithm and its asymptotically-optimal counterpart called RRT* are popular algorithms used in real-life applications due to its desirable properties. Such algorithms are inherently iterative, but certain modules such as the collision-checking procedure can be parallelized providing significant speedup with respect to sequential implementations. In this paper, the RRT and RRT* algorithms have been adapted to a bioinspired computational framework called Membrane Computing whose models of computation, a.k.a. P systems, run in a non-deterministic and massively parallel way. A large number of robotic applications are currently using a variant of P systems called Enzymatic Numerical P systems (ENPS) for reactive controlling, but there is a lack of solutions for motion planning in the framework. The novel models in this work have been designed using the ENPS framework. In order to test and validate the ENPS models for RRT and RRT*, we present two ad-hoc implementations able to emulate the computation of the models using OpenMP and CUDA. Finally, we show the speedup of our solutions with respect to sequential baseline implementations. The results show a speedup up to 6x using OpenMP with 8 cores against the sequential implementation and up to 24x using CUDA against the best multi-threading configuration.

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Section: Resultsmentioning

confidence: 91%

“…The task of detecting and interpreting a moving object, 1 Corresponding Author: School of Computer Science, Jubilee Campus, Wollaton Road, Nottingham NG8 1BB, United Kingdom, Email: ferrante.neri@nottingham.ac.uk. that is motion tracking, is fundamental for the correct functioning of a robot, [8,76].…”

Section: Introductionmentioning

confidence: 99%

A membrane parallel rapidly-exploring random tree algorithm for robotic motion planning

Pérez–Hurtado

Amor

Zhang

et al. 2020

ICA

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“…In the aforementioned multicamera tracking methods, object tracking is performed using the overlapped images captured by fixed cameras. Benito-Picazo et al [17] use fixed cameras and PTZ cameras to capture overlapped images for object tracking. The methods use a surveillance system that employs both static and active cameras with panning, tilting and zooming functions.…”

Section: Cameras Networkmentioning

confidence: 99%

Cooperative People Tracking by Distributed Cameras Network

Chen

Chiu

et al. 2021

Electronics

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In the application of video surveillance, reliable people detection and tracking are always challenging tasks. The conventional single-camera surveillance system may encounter difficulties such as narrow-angle of view and dead space. In this paper, we proposed multi-cameras network architecture with an inter-camera hand-off protocol for cooperative people tracking. We use the YOLO model to detect multiple people in the video scene and incorporate the particle swarm optimization algorithm to track the person movement. When a person leaves the area covered by a camera and enters an area covered by another camera, these cameras can exchange relevant information for uninterrupted tracking. The motion smoothness (MS) metrics is proposed for evaluating the tracking quality of multi-camera networking system. We used a three-camera system for two persons tracking in overlapping scene for experimental evaluation. Most tracking person offsets at different frames were lower than 30 pixels. Only 0.15% of the frames showed abrupt increases in offsets pixel. The experiment results reveal that our multi-camera system achieves robust, smooth tracking performance.

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“…It is mandatory to continuously provide excellent viewpoints by modifying the camera's angles [23] to monitor people who are undergoing physical rehabilitation programs. RGB-D sensors must be placed in the best positions in an intelligent manner to acquire images of the most relevant parts of the patients' bodies.…”

Section: Introductionmentioning

confidence: 99%

Advanced Trajectory Generator for Two Carts with RGB-D Sensor on Circular Rail

Panduro

Segura

Belmonte

et al. 2019

Understanding the Brain Function and Emotions

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This paper presents a motorised circular rail that generates the motion of two carts with an RGB-D sensor each. The objective of both carts' trajectory generation is to track a person's physical rehabilitation exercises from two points of view and his/her emotional state from one of these viewpoints. The person is moving freely his/her position and posture within the circle drawn by the motorised rail. More specifically, this paper describes the calculation of trajectories for safe motion of the two carts on the motorised circular rail in detail. Lastly, a study case is offered to show the performance of the described control algorithms for trajectory generation.

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Motion detection with low cost hardware for PTZ cameras

Cited by 8 publications

References 36 publications

A membrane parallel rapidly-exploring random tree algorithm for robotic motion planning

A membrane parallel rapidly-exploring random tree algorithm for robotic motion planning

Cooperative People Tracking by Distributed Cameras Network

Advanced Trajectory Generator for Two Carts with RGB-D Sensor on Circular Rail

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