International Conference on Computer and Knowledge Engineering

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Towards Efficient Video Object Detection on Embedded Devices

Authors :

Mohammad Hajizadeh¹ Adel Rahmani² Mohammad Sabokrou³

1- School of Computer Engineering Iran University of Science and Technology 2- School of Computer Engineering Iran University of Science and Technology, Tehran, Iran 3- School of Computer Science IPM Institute for Research in Fundamental Sciences

Keywords :

Object Detection،Embedded Device،Deep Neural Networks

Abstract :

The challenge of adapting various object recognition techniques from still images to videos remains unsolved. When applied to videos, methods that are specifically designed for images do not perform well due to several complications. These include blurriness, shifting or ambiguous locations, subpar quality, and other similar concerns. In addition, a lack of effective long-term memory in video object detection has yet to be addressed. It is widely recognized that consecutive frames in a video tend to produce highly similar results in most cases. Therefore, this characteristic can be exploited to improve performance. Moreover, the information contained in a series of sequential or non-consecutive frames exceeds that of a single frame. In our research, we have introduced a novel recurrent cell for feature propagation and have determined the optimal layer placement to augment the memory span. This has resulted in superior precision compared to methods presented in previous research. Furthermore, hardware constraints may exacerbate this issue. Therefore, we have focused on implementing and improving the effectiveness of these techniques on embedded devices. Our approach has yielded impressive results, with a 67.5% mAP accuracy on the real-time ImageNet VID dataset for mobile devices at a rate of 62 fps.

Papers List

List of archived papers

Introducing E4MT and LMBNC: Persian pre-processing utilities

Zakieh Shakeri - Mehran Ziabary - Behrooz Vedadian - Fatemeh Azadi - Saeed Torabzadeh - Arian Atefi

AIRSPAN-X: Federated XGBoost with Sequential Anomaly Detection for Explainable Urban Air Quality Prediction

Saghar Shafaati - S. Hossein Erfani

Simulation-Based Data Augmentation for Apple Leaf Disease Using Statistical Moments and HSV Color Features

Seyedeh Maryam Moosavi - Morteza Gholipour - Yasser Baleghi

Fine-tuned Generative Adversarial Network-based Model for Medical Image Super-Resolution

Alireza Aghelan - Modjtaba Rouhani

A Deep CNN Model Based Ensemble Approach for Semantic and Instance Segmentation of Indoor Environment

Sajad Rezaei - Jafar Tanha - Zahra Jafari - SeyedEhsan Roshan - Mohammad-Amin Memar Kochebagh

A Framework for Automated Cardiovascular Magnetic Resonance Image Quality Scoring based on EuroCMR Registry Criteria

Shahabedin Nabavi - Mohsen Ebrahimi Moghaddam - Ahmad Ali Abin - Alejandro Frangi

A Comparative Analysis of Clinical Note Categories for Mortality Prediction in ICU Patients

Maryam Karrabi - Mohsen Kahani - Mina Afzali - Nadieh Armin

Attention Transfer in Self-Regulated Networks for Recognizing Human Actions from Still Images

Masoumeh Chapariniya - Sara Vesali Barazande - Seyed Sajad Ashrafi - Shahriar B.Shokouhi

TD-PINNs: Efficient Shared-Memory Parallelization of Physics-Informed Neural Networks for Time-Dependent PDEs

Mahdi Movahedian Moghaddam - Kourosh Parand

YOLOatt-Med: YOLO-Based Attention Mechanism for Medical Image Classification

Fatemeh Naserizadeh - Erfan Akbarnezhad Sany - Parsa Sinichi - Seyyed Abed Hosseini