A tracking algorithm based on ORB

Meng, Fanqing; You, Fei

doi:10.1109/mec.2013.6885245

Cited by 11 publications

(2 citation statements)

References 6 publications

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“…The Hamming distance for each keypoint descriptor and the descriptor in the database is computed. The Hamming distance between two descriptors S 1 ,S 2 is computed using Equation ( 23) [37]:…”

Section: Orbmentioning

confidence: 99%

An Efficient System for Automatic Blood Type Determination Based on Image Matching Techniques

et al. 2021

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This paper presents a fast and accurate system to determine the type of blood automatically based on image processing. Blood type determination is important in emergency situations, where there is a need for blood transfusion to save lives. The traditional blood determination techniques are performed manually by a specialist in medical labs, where the result requires a long time or may be affected by human error. This may cause serious consequences or even endanger people’s lives. The proposed approach performs blood determination in real-time with low cost using any available mobile device equipped with a camera. A total of 500 blood samples were processed in this study using different image matching techniques including oriented fast and rotated brief (ORB), scale invariant feature transform (SIFT), and speed-up robust feature (SURF). The evaluation results show that our proposed system, which adopts the ORB algorithm, is the fastest and the most accurate among the state-of-the-art systems. It can achieve an accuracy of 99.6% in an average time of 250 ms.

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Section: Orbmentioning

confidence: 99%

An Efficient System for Automatic Blood Type Determination Based on Image Matching Techniques

et al. 2021

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“…• ORB -Oriented FAST and rotated BRIEF (ORB) was introduced in 2011 by Ethan Rublee [9]. It is an effective algorithm for the process of image processing and also object detection [7]. As the name suggests it is a fusion of the two other algorithms mentioned here.…”

Section: Understanding Different Algorithmsmentioning

confidence: 99%

Original vs Counterfeit Indian Currency Detection

et al. 2020

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Currency is used to carry out not only business but also for various other transactions to get access to various services and commodities. There are a total of 7 denominations for the Indian currency each with unique features to distinguish them from each other and with various and distinct security features to prevent them from fraudulent copying. However,with the evolution of technology, there is also an increase in the ways in which fake forms of these currencies are created. These fake or counterfeit notes have various ill-effect on society. The proposed system will be used to check the genuine Indian currency notes and to find the denomination of the currency note. Comparative study for various image processing algorithms was conducted to identify and select the one which will be able to extract more prominent features,and is also better in terms of processing time,outlier rejection, efficiency in computation and in feature matching. After which a real time system is created for currency detection in real time.

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Indoor localisation through object detection within multiple environments utilising a single wearable camera

et al. 2016

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The recent growth in the wearable sensor market has stimulated new opportunities within the domain of Ambient Assisted Living, providing unique methods of collecting occupant information. This approach leverages contemporary wearable technology, Google Glass, to facilitate a unique first-person view of the occupants immediate environment. Machine vision techniques are employed to determine an occupant’s location via environmental object detection. This method provides additional secondary benefits such as first person tracking within the environment and lack of required sensor interaction to determine occupant location. Object recognition is performed using the Oriented Features from Accelerated Segment Test and Rotated Binary Robust Independent Elementary Features algorithm with a K-Nearest Neighbour matcher to match the saved key-points of the objects to the scene. To validate the approach, an experimental set-up consisting of three ADL routines, each containing at least ten activities, ranging from drinking water to making a meal were considered. Ground truth was obtained from manually annotated video data and the approach was previously benchmarked against a common method of indoor localisation that employs dense sensor placement in order to validate the approach resulting in a recall, precision, and F-measure of 0.82, 0.96, and 0.88 respectively. This paper will go on to assess to the viability of applying the solution to differing environments, both in terms of performance and along with a qualitative analysis on the practical aspects of installing such a system within differing environments.

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A tracking algorithm based on ORB

Cited by 11 publications

References 6 publications

An Efficient System for Automatic Blood Type Determination Based on Image Matching Techniques

An Efficient System for Automatic Blood Type Determination Based on Image Matching Techniques

Original vs Counterfeit Indian Currency Detection

Indoor localisation through object detection within multiple environments utilising a single wearable camera

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