A Robust Visual Object Tracking Approach on a Mobile Device

Mohammed, Abdulmalik Danlami; Morris, Tim

doi:10.1007/978-3-642-55032-4_19

Cited by 3 publications

(1 citation statement)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The camshift algorithm is used to preprocess the frames, a wide variety of applications can found for the camshift algorithm [37,38,39] including object tracking and frame rate and size reduction by only capturing the ROI areas. In our approach, we have used the camshift algorithm to reduce the number of frames.…”

Section: A Preprocessing Of Video Usingmentioning

confidence: 99%

Artificial Bee Colony Algorithm Optimization for Video Summarization on VSUMM Dataset

Paramanantham¹,

Sureshkumar²

2020

IJACSA

View full text Add to dashboard Cite

This paper attempts to prove that the Artificial Bee Colony algorithm can be used as an optimization algorithm in sparse-land setup to solve Video Summarization. The critical challenge in doing quasi(real-time) video summarization is still time-consuming with ANN-based methods, as these methods require training time. By doing video summarization in a quasi (real-time), we can solve other challenges like anomaly detection and Online Video Highlighting. A simple threshold function is tested to see the reconstruction error of the current frame given the previous 50 frames from the dictionary. The frames with higher threshold errors form the video summarization. In this work, we have used Image histogram, HOG, HOOF, and Canny edge features as features to the ABC algorithm. We have used Matlab 2014a for doing the feature extraction and ABC algorithm for VS. The results are compared to the existing methods. The evaluation scores are calculated on the VSUMM dataset for all the 50 videos against the two user summaries. This research answers how the ABC algorithm can be used in a sparse-land setup to solve video summarization. Further studies are required to understand the performance evaluation scores as we change the threshold function.

show abstract

Section: A Preprocessing Of Video Usingmentioning

confidence: 99%

Artificial Bee Colony Algorithm Optimization for Video Summarization on VSUMM Dataset

Paramanantham¹,

Sureshkumar²

2020

IJACSA

View full text Add to dashboard Cite

show abstract

Applications in Face Recognition Access Control Manufacturing

Wang

Chen

Yao

2022

Five-Layer Intelligence of the Machine Brain

View full text Add to dashboard Cite

Recognition algorithm of landmark for quadrotors aircraft based on image feature of corner points

Luo

Miao

Wang

2015

2015 IEEE International Conference on Information and Automation

View full text Add to dashboard Cite

To solve the problem of lateral navigation control of quadrotors aircraft, a new recognition algorithm of landmark with multi angle observations is proposed. According to the characteristics of landmark, the image is divided into two parts with circle and character H. The analysis reveals a geometric correlation exits between corner points of character H .The correlation has a low sensitivity to rotation post and environment. The results show that recognition algorithm based on corner points not only keeps the real time performance but also detects landmarks at any degree of rotation in the 2D image plane from the air, and outperforms linear feature algorithms. In the end, results of recognition experiments verify the effectiveness of the approach. And the algorithms meets the demands of lateral navigation control of quadrotors aircraft with such advantages as high accuracy, good reliability.

show abstract

A Robust Visual Object Tracking Approach on a Mobile Device

Cited by 3 publications

References 11 publications

Artificial Bee Colony Algorithm Optimization for Video Summarization on VSUMM Dataset

Artificial Bee Colony Algorithm Optimization for Video Summarization on VSUMM Dataset

Applications in Face Recognition Access Control Manufacturing

Recognition algorithm of landmark for quadrotors aircraft based on image feature of corner points

Contact Info

Product

Resources

About