In the context of modernization and development of new information and communications technology,... more In the context of modernization and development of new information and communications technology, ultra-connected world has become a strategic element. Wireless communication technologies have enabled a kaleidoscopic range of applications that are revolutionizing many aspects of business and public services. Connected cars themselves as new born of new technologies, are the next frontiers for the automobile revolution and the key to the evolution towards the next generation of intelligent transport systems that enable information sharing and communication between vehicles and their internal and external environment. Moreover, connected cars are the main use cases of internet of things (IOT), yet they are the least understood in terms of cyber security. And as with all things using the internet infrastructure for the exchange of information, communications of connected cars are sensitive to various security issues and have some great concerns with privacy and data confidentialities. In this article, we focus on wireless technologies and potential challenges to provide a communication's vehicle-to-vehicle(V2V) or vehicle-to-X(V2X). In particular, we discuss the challenges and review the state-of-the-art wireless solutions for internet of vehicle(IOV). We also identify future research issues for building connected vehicles and solutions which have been proposed by several researchers.
2021 Fifth International Conference On Intelligent Computing in Data Sciences (ICDS), 2021
Falls are the most leading cause of accidental injury deaths worldwide, therefore, it poses a rea... more Falls are the most leading cause of accidental injury deaths worldwide, therefore, it poses a real challenge for the prevention of life-threatening conditions in geriatrics. The most damaged community is the ever-growing aging population. For this reason, there are considerable demands to distinguish a dangerous posture such as fall in real-time. Here we provide a literature review of conducted work on elderly fall detection and prediction mentioning the main methods to recognize human posture including computer vision-based and wearable sensor-based. We approached these perspectives: sensor fusion, Datasets, approaches proposition. In conclusion, our survey summarizes the progress achieved in the five past years to help the researchers in this field to spot areas where further effort would be beneficial and innovative.
Over the past few decades, extensive death of women due to breast cancer has precipitated the nee... more Over the past few decades, extensive death of women due to breast cancer has precipitated the need for the best classification of breast cancer. Classification of breast cancer can help in choose the appropriate and the convenient treatment. Many researchers have studied the breast cancer using artificial neural network model (ANN) for his ability to visualize high-dimensional data. The use of learning machine and artificial intelligence techniques has revolutionized the process of diagnosis and prognosis of the breast cancer. However, there are still some problems applying ANN algorithm such as longer training time and lower classification accuracy. To overcome these problems, the SOM model based on Distance travelled by neurons (DSOM) has been proposed, using the Wisconsin diagnostic breast Cancer datasets (WDBC) to distinguish between different types of breast cancer. The data set consists of nine attributes that represent the input layer to the neural network. The neural network will classify the input vectors into two classes of cancer type (benign and malignant). The proposed approach tested on the database, resulted in 97 % succession rate of classification. We can concluded that our approach seems an efficient method to classify in medical applications and especially for the breast cancer classification.
Communications in computer and information science, 2018
The use of general descriptive names, registered names, trademarks, service marks, etc. in this p... more The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use.
In the last years, new data sources appeared: social networks, mobile, internet of things, open D... more In the last years, new data sources appeared: social networks, mobile, internet of things, open Data, etc., and therefore data are rapidly increasing. These data is voluminous, various, and difficult to measure and analyze, which appears the concept of Big Data. The vast amount of data makes the ETL (Extract-Transform-Load) process heavy in data warehousing, renders the data mining process more complex, and makes the slow loading of data in database management systems. The solution to make these process more efficient is the use of parallelization technologies, many researchers opt for the use of MapReduce paradigm for its flexibility and powerful. In this paper, we provide an overview of state of the art in MapReduce research and we present its various axis.
International journal of computer applications in technology, 2019
Cloud computing is a broad concept pertaining to different service models following the utility c... more Cloud computing is a broad concept pertaining to different service models following the utility computing model. Owing to its numerous advantages like high resource elasticity, time improvement, IT maintenance cost reduction, and simplicity, cloud computing paradigm interests many customers. However, notions introduced by the cloud such as the multi-tenancy concept, the computation outsourcing, and the distributed resources increase the security concerns and make trust in cloud providers a critical security challenge. This paper suggests a new method for enhancing the confidentiality of data in the cloud. As data in the cloud has not the same sensitivity, encrypting it with the same algorithms can lead to a lack of security or of resources. The paper proposes to classify data according to a sensitivity level in order to give a suitable security model for each data. By this process, we optimise the use of security mechanisms and the resources consumption.
International journal of computer applications, Jul 15, 2016
Sharing data using cloud computing can be a good solution to profit from reduced costs, scalabili... more Sharing data using cloud computing can be a good solution to profit from reduced costs, scalability, flexibility and more advantages that user can get from the cloud infrastructure. But when the object shared consists of sensitive or personnel data, the security concerns increase. Problems related to the lack of data confidentiality and integrity represent the number one problem encountered in cloud infrastructure and that restrains users and a number of organizations to benefit from the cloud"s services. In this paper we discuss the requirements needed to secure data in cloud environment and we propose a new approach to enhance the security of the data shared in cloud storage. Our method is based on cryptographic models. It is confidential, flexible and it reduces time of computation by adopting simple and efficient key management process and encryption schemes.
Cloud computing is a wide architecture based on diverse models for providing different services o... more Cloud computing is a wide architecture based on diverse models for providing different services of software and hardware. Cloud computing paradigm attracts different users because of its several benefits such as high resource elasticity, expense reduction, scalability and simplicity which provide significant preserving in terms of investment and work force. However, the new approaches introduced by the cloud, related to computation outsourcing, distributed resources, multi-tenancy concept, high dynamism of the model, data warehousing and the nontransparent style of cloud increase the security and privacy concerns and makes building and handling trust among cloud service providers and consumers a critical security challenge. This paper proposes a new approach to improve security of data in cloud computing. It suggests a classification model to categorize data before being introduced into a suitable encryption system according to the category. Since data in cloud has not the same sensitivity level, encrypting it with the same algorithms can lead to a lack of security or of resources. By this method we try to optimize the resources consumption and the computation cost while ensuring data confidentiality.
Cloud computing has emerged as a new computing paradigm where all IT infrastructure can be outsou... more Cloud computing has emerged as a new computing paradigm where all IT infrastructure can be outsourced and working as on premise. It offers numerous advantages both for customers and providers and especially at the cost level that is typically low compared to buying your own resources, configuring and managing them. One of the tremendous services is the data sharing and the data storage. Customers can outsource a huge number of data in cloud without having to worry about the capacity of memory or the size of data as cloud system manage the scalability of servers needed to contains your data. Cloud is flexible, scalable and dynamic so don't worry about capacities. But, one of the predominant concerns encountered in cloud and that can change your mind about this nice view, is security. As more and more sensitive data and personal information placed in the cloud, security concerns grow up. Building trust in providers it is not an easy task with an amount of outages and threats declared since adoption of cloud computing. In this paper, we give a new approach to enhance the security of data outsourced in cloud environment. The approach is based on Cipher Policy-Attribute Based Encryption (CP-ABE) scheme. It consists of encrypting data before outsourcing it and controlling the access to it by encryption. Our method offers scalability, flexibility and fine grained access control of data in cloud. Also, it provides an efficient manner to share confidential data on cloud servers.
Cloud computing has emerged as a new computing paradigm where all IT infrastructure can be outsou... more Cloud computing has emerged as a new computing paradigm where all IT infrastructure can be outsourced and working as on premise. It offers numerous advantages both for customers and providers and especially at the cost level that is typically low compared to buying your own resources, configuring and managing them. One of the tremendous services is the data sharing and the data storage. Customers can outsource a huge number of data in cloud without having to worry about the capacity of memory or the size of data as cloud system manage the scalability of servers needed to contains your data. Cloud is flexible, scalable and dynamic so don't worry about capacities. But, one of the predominant concerns encountered in cloud and that can change your mind about this nice view, is security. As more and more sensitive data and personal information placed in the cloud, security concerns grow up. Building trust in providers it is not an easy task with an amount of outages and threats declared since adoption of cloud computing. In this paper, we give a new approach to enhance the security of data outsourced in cloud environment. The approach is based on Cipher Policy-Attribute Based Encryption (CP-ABE) scheme. It consists of encrypting data before outsourcing it and controlling the access to it by encryption. Our method offers scalability, flexibility and fine grained access control of data in cloud. Also, it provides an efficient manner to share confidential data on cloud servers.
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
Underground mining operations present critical safety hazards due to limited visibility and blind... more Underground mining operations present critical safety hazards due to limited visibility and blind areas, which can lead to collisions between mobile machines and vehicles or persons, causing accidents and fatalities. This paper aims to survey the existing literature on anti-collision systems based on computer vision for pedestrian detection in underground mines, categorize them based on the types of sensors used, and evaluate their effectiveness in deep underground environments. A systematic review of the literature was conducted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to identify relevant research work on anti-collision systems for underground mining. The selected studies were analyzed and categorized based on the types of sensors used and their advantages and limitations in deep underground environments. This study provides an overview of the anti-collision systems used in underground mining, including cameras and lidar ...
The Advance of web-based technologies have brought radical changes to web site design and web ser... more The Advance of web-based technologies have brought radical changes to web site design and web service usage, primarily in terms of interactive contents and user engagement in collaboration and information sharing. In nutshell the web has been transformed from static media to the preferred commu‐ nication media where the user is a key player in the creation of his experiences. The increase in the popularity of social networks on the Web has shaken up tradi‐ tional models in different areas, including learning. Many individuals have resorted to social networking to educate themselves. Such learning is close to natural learning, the learner is autonomous to draw the pathway which best suits his individual needs in order to upgrade his skills. Several training organizations use the Twitter platform to announce the training they provide. We conduct an experiment on twitters data which are related to the training themes in Big Data and Data Science, we perform an exploratory analysis and extract the top group of connected hashtags using the Graph X library provided by the Spark frame‐ work. Data that come from the Twitter platform is produced at high speed and in a complex structure. This leads us to use a distributed infrastructure based on two efficient frameworks Apache Hadoop and Spark. Data ingestion layer is built by combining two frameworks Apache Flume and Kafka.
International Journal of Electrical and Computer Engineering (IJECE), 2017
Segmentation of the video sequence by detecting shot changes is essential for video analysis, ind... more Segmentation of the video sequence by detecting shot changes is essential for video analysis, indexing and retrieval. In this context, a shot boundary detection algorithm is proposed in this paper based on the scale invariant feature transform (SIFT). The first step of our method consists on a top down search scheme to detect the locations of transitions by comparing the ratio of matched features extracted via SIFT for every RGB channel of video frames. The overview step provides the locations of boundaries. Secondly, a moving average calculation is performed to determine the type of transition. The proposed method can be used for detecting gradual transitions and abrupt changes without requiring any training of the video content in advance. Experiments have been conducted on a multi type video database and show that this algorithm achieves well performances.
International Journal of Computer Applications, 2014
Text supply crucial suggestions for understanding video content, also the information that the te... more Text supply crucial suggestions for understanding video content, also the information that the text convey is much more concise than corresponding audio or video. The reason is that we need language knowledge to understand the text, and the knowledge itself does not need to be embedded in the text data. Text streams contain very rich semantic information. How to effectively extract information from text is an important component in video content analysis and semantics research. In this paper, a new morphology-based method for text detection in image and video is proposed. It consists of three major stages. In the first stage, the input color image is converted to gray-scale, a morphological binary map is generated by calculating the difference between the closing image and the opening image, and a binarization is performed. In the second stage, candidate regions are connected by using a morphological dilation and erosion operations. In the last stage, the extracted regions are verified based on characteristic of text regions to eliminate non text regions.
Nowadays, huge amount of multimedia repositories<br> make the browsing, retrieval and deliv... more Nowadays, huge amount of multimedia repositories<br> make the browsing, retrieval and delivery of video contents very slow<br> and even difficult tasks. Video summarization has been proposed to<br> improve faster browsing of large video collections and more efficient<br> content indexing and access. In this paper, we focus on approaches to<br> video summarization. The video summaries can be generated in many<br> different forms. However, two fundamentals ways to generate<br> summaries are static and dynamic. We present different techniques<br> for each mode in the literature and describe some features used for<br> generating video summaries. We conclude with perspective for<br> further research.
In the context of modernization and development of new information and communications technology,... more In the context of modernization and development of new information and communications technology, ultra-connected world has become a strategic element. Wireless communication technologies have enabled a kaleidoscopic range of applications that are revolutionizing many aspects of business and public services. Connected cars themselves as new born of new technologies, are the next frontiers for the automobile revolution and the key to the evolution towards the next generation of intelligent transport systems that enable information sharing and communication between vehicles and their internal and external environment. Moreover, connected cars are the main use cases of internet of things (IOT), yet they are the least understood in terms of cyber security. And as with all things using the internet infrastructure for the exchange of information, communications of connected cars are sensitive to various security issues and have some great concerns with privacy and data confidentialities. In this article, we focus on wireless technologies and potential challenges to provide a communication's vehicle-to-vehicle(V2V) or vehicle-to-X(V2X). In particular, we discuss the challenges and review the state-of-the-art wireless solutions for internet of vehicle(IOV). We also identify future research issues for building connected vehicles and solutions which have been proposed by several researchers.
2021 Fifth International Conference On Intelligent Computing in Data Sciences (ICDS), 2021
Falls are the most leading cause of accidental injury deaths worldwide, therefore, it poses a rea... more Falls are the most leading cause of accidental injury deaths worldwide, therefore, it poses a real challenge for the prevention of life-threatening conditions in geriatrics. The most damaged community is the ever-growing aging population. For this reason, there are considerable demands to distinguish a dangerous posture such as fall in real-time. Here we provide a literature review of conducted work on elderly fall detection and prediction mentioning the main methods to recognize human posture including computer vision-based and wearable sensor-based. We approached these perspectives: sensor fusion, Datasets, approaches proposition. In conclusion, our survey summarizes the progress achieved in the five past years to help the researchers in this field to spot areas where further effort would be beneficial and innovative.
Over the past few decades, extensive death of women due to breast cancer has precipitated the nee... more Over the past few decades, extensive death of women due to breast cancer has precipitated the need for the best classification of breast cancer. Classification of breast cancer can help in choose the appropriate and the convenient treatment. Many researchers have studied the breast cancer using artificial neural network model (ANN) for his ability to visualize high-dimensional data. The use of learning machine and artificial intelligence techniques has revolutionized the process of diagnosis and prognosis of the breast cancer. However, there are still some problems applying ANN algorithm such as longer training time and lower classification accuracy. To overcome these problems, the SOM model based on Distance travelled by neurons (DSOM) has been proposed, using the Wisconsin diagnostic breast Cancer datasets (WDBC) to distinguish between different types of breast cancer. The data set consists of nine attributes that represent the input layer to the neural network. The neural network will classify the input vectors into two classes of cancer type (benign and malignant). The proposed approach tested on the database, resulted in 97 % succession rate of classification. We can concluded that our approach seems an efficient method to classify in medical applications and especially for the breast cancer classification.
Communications in computer and information science, 2018
The use of general descriptive names, registered names, trademarks, service marks, etc. in this p... more The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use.
In the last years, new data sources appeared: social networks, mobile, internet of things, open D... more In the last years, new data sources appeared: social networks, mobile, internet of things, open Data, etc., and therefore data are rapidly increasing. These data is voluminous, various, and difficult to measure and analyze, which appears the concept of Big Data. The vast amount of data makes the ETL (Extract-Transform-Load) process heavy in data warehousing, renders the data mining process more complex, and makes the slow loading of data in database management systems. The solution to make these process more efficient is the use of parallelization technologies, many researchers opt for the use of MapReduce paradigm for its flexibility and powerful. In this paper, we provide an overview of state of the art in MapReduce research and we present its various axis.
International journal of computer applications in technology, 2019
Cloud computing is a broad concept pertaining to different service models following the utility c... more Cloud computing is a broad concept pertaining to different service models following the utility computing model. Owing to its numerous advantages like high resource elasticity, time improvement, IT maintenance cost reduction, and simplicity, cloud computing paradigm interests many customers. However, notions introduced by the cloud such as the multi-tenancy concept, the computation outsourcing, and the distributed resources increase the security concerns and make trust in cloud providers a critical security challenge. This paper suggests a new method for enhancing the confidentiality of data in the cloud. As data in the cloud has not the same sensitivity, encrypting it with the same algorithms can lead to a lack of security or of resources. The paper proposes to classify data according to a sensitivity level in order to give a suitable security model for each data. By this process, we optimise the use of security mechanisms and the resources consumption.
International journal of computer applications, Jul 15, 2016
Sharing data using cloud computing can be a good solution to profit from reduced costs, scalabili... more Sharing data using cloud computing can be a good solution to profit from reduced costs, scalability, flexibility and more advantages that user can get from the cloud infrastructure. But when the object shared consists of sensitive or personnel data, the security concerns increase. Problems related to the lack of data confidentiality and integrity represent the number one problem encountered in cloud infrastructure and that restrains users and a number of organizations to benefit from the cloud"s services. In this paper we discuss the requirements needed to secure data in cloud environment and we propose a new approach to enhance the security of the data shared in cloud storage. Our method is based on cryptographic models. It is confidential, flexible and it reduces time of computation by adopting simple and efficient key management process and encryption schemes.
Cloud computing is a wide architecture based on diverse models for providing different services o... more Cloud computing is a wide architecture based on diverse models for providing different services of software and hardware. Cloud computing paradigm attracts different users because of its several benefits such as high resource elasticity, expense reduction, scalability and simplicity which provide significant preserving in terms of investment and work force. However, the new approaches introduced by the cloud, related to computation outsourcing, distributed resources, multi-tenancy concept, high dynamism of the model, data warehousing and the nontransparent style of cloud increase the security and privacy concerns and makes building and handling trust among cloud service providers and consumers a critical security challenge. This paper proposes a new approach to improve security of data in cloud computing. It suggests a classification model to categorize data before being introduced into a suitable encryption system according to the category. Since data in cloud has not the same sensitivity level, encrypting it with the same algorithms can lead to a lack of security or of resources. By this method we try to optimize the resources consumption and the computation cost while ensuring data confidentiality.
Cloud computing has emerged as a new computing paradigm where all IT infrastructure can be outsou... more Cloud computing has emerged as a new computing paradigm where all IT infrastructure can be outsourced and working as on premise. It offers numerous advantages both for customers and providers and especially at the cost level that is typically low compared to buying your own resources, configuring and managing them. One of the tremendous services is the data sharing and the data storage. Customers can outsource a huge number of data in cloud without having to worry about the capacity of memory or the size of data as cloud system manage the scalability of servers needed to contains your data. Cloud is flexible, scalable and dynamic so don't worry about capacities. But, one of the predominant concerns encountered in cloud and that can change your mind about this nice view, is security. As more and more sensitive data and personal information placed in the cloud, security concerns grow up. Building trust in providers it is not an easy task with an amount of outages and threats declared since adoption of cloud computing. In this paper, we give a new approach to enhance the security of data outsourced in cloud environment. The approach is based on Cipher Policy-Attribute Based Encryption (CP-ABE) scheme. It consists of encrypting data before outsourcing it and controlling the access to it by encryption. Our method offers scalability, flexibility and fine grained access control of data in cloud. Also, it provides an efficient manner to share confidential data on cloud servers.
Cloud computing has emerged as a new computing paradigm where all IT infrastructure can be outsou... more Cloud computing has emerged as a new computing paradigm where all IT infrastructure can be outsourced and working as on premise. It offers numerous advantages both for customers and providers and especially at the cost level that is typically low compared to buying your own resources, configuring and managing them. One of the tremendous services is the data sharing and the data storage. Customers can outsource a huge number of data in cloud without having to worry about the capacity of memory or the size of data as cloud system manage the scalability of servers needed to contains your data. Cloud is flexible, scalable and dynamic so don't worry about capacities. But, one of the predominant concerns encountered in cloud and that can change your mind about this nice view, is security. As more and more sensitive data and personal information placed in the cloud, security concerns grow up. Building trust in providers it is not an easy task with an amount of outages and threats declared since adoption of cloud computing. In this paper, we give a new approach to enhance the security of data outsourced in cloud environment. The approach is based on Cipher Policy-Attribute Based Encryption (CP-ABE) scheme. It consists of encrypting data before outsourcing it and controlling the access to it by encryption. Our method offers scalability, flexibility and fine grained access control of data in cloud. Also, it provides an efficient manner to share confidential data on cloud servers.
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
Underground mining operations present critical safety hazards due to limited visibility and blind... more Underground mining operations present critical safety hazards due to limited visibility and blind areas, which can lead to collisions between mobile machines and vehicles or persons, causing accidents and fatalities. This paper aims to survey the existing literature on anti-collision systems based on computer vision for pedestrian detection in underground mines, categorize them based on the types of sensors used, and evaluate their effectiveness in deep underground environments. A systematic review of the literature was conducted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to identify relevant research work on anti-collision systems for underground mining. The selected studies were analyzed and categorized based on the types of sensors used and their advantages and limitations in deep underground environments. This study provides an overview of the anti-collision systems used in underground mining, including cameras and lidar ...
The Advance of web-based technologies have brought radical changes to web site design and web ser... more The Advance of web-based technologies have brought radical changes to web site design and web service usage, primarily in terms of interactive contents and user engagement in collaboration and information sharing. In nutshell the web has been transformed from static media to the preferred commu‐ nication media where the user is a key player in the creation of his experiences. The increase in the popularity of social networks on the Web has shaken up tradi‐ tional models in different areas, including learning. Many individuals have resorted to social networking to educate themselves. Such learning is close to natural learning, the learner is autonomous to draw the pathway which best suits his individual needs in order to upgrade his skills. Several training organizations use the Twitter platform to announce the training they provide. We conduct an experiment on twitters data which are related to the training themes in Big Data and Data Science, we perform an exploratory analysis and extract the top group of connected hashtags using the Graph X library provided by the Spark frame‐ work. Data that come from the Twitter platform is produced at high speed and in a complex structure. This leads us to use a distributed infrastructure based on two efficient frameworks Apache Hadoop and Spark. Data ingestion layer is built by combining two frameworks Apache Flume and Kafka.
International Journal of Electrical and Computer Engineering (IJECE), 2017
Segmentation of the video sequence by detecting shot changes is essential for video analysis, ind... more Segmentation of the video sequence by detecting shot changes is essential for video analysis, indexing and retrieval. In this context, a shot boundary detection algorithm is proposed in this paper based on the scale invariant feature transform (SIFT). The first step of our method consists on a top down search scheme to detect the locations of transitions by comparing the ratio of matched features extracted via SIFT for every RGB channel of video frames. The overview step provides the locations of boundaries. Secondly, a moving average calculation is performed to determine the type of transition. The proposed method can be used for detecting gradual transitions and abrupt changes without requiring any training of the video content in advance. Experiments have been conducted on a multi type video database and show that this algorithm achieves well performances.
International Journal of Computer Applications, 2014
Text supply crucial suggestions for understanding video content, also the information that the te... more Text supply crucial suggestions for understanding video content, also the information that the text convey is much more concise than corresponding audio or video. The reason is that we need language knowledge to understand the text, and the knowledge itself does not need to be embedded in the text data. Text streams contain very rich semantic information. How to effectively extract information from text is an important component in video content analysis and semantics research. In this paper, a new morphology-based method for text detection in image and video is proposed. It consists of three major stages. In the first stage, the input color image is converted to gray-scale, a morphological binary map is generated by calculating the difference between the closing image and the opening image, and a binarization is performed. In the second stage, candidate regions are connected by using a morphological dilation and erosion operations. In the last stage, the extracted regions are verified based on characteristic of text regions to eliminate non text regions.
Nowadays, huge amount of multimedia repositories<br> make the browsing, retrieval and deliv... more Nowadays, huge amount of multimedia repositories<br> make the browsing, retrieval and delivery of video contents very slow<br> and even difficult tasks. Video summarization has been proposed to<br> improve faster browsing of large video collections and more efficient<br> content indexing and access. In this paper, we focus on approaches to<br> video summarization. The video summaries can be generated in many<br> different forms. However, two fundamentals ways to generate<br> summaries are static and dynamic. We present different techniques<br> for each mode in the literature and describe some features used for<br> generating video summaries. We conclude with perspective for<br> further research.
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