VISION BASED MULTIPLE OBJECT TRACKING AND LOCALIZATION FROM AUTONOMOUS A REAL VEHICLE Abstract In recent years, an investigation of underwater world is elaborated to study about unknown objects deposited in deep sea region and identify the right place to locate natural disaster detective system. Before it starts, a camera mounted vehicle is sending to capture image of long depth area. Due to water impartibility, a poor quality of image is received with conveys less significant details about the region. It can be resolved by using adaptive filtering techniques. However, once, it recognized the object correctly, then, the object should be recovered from deep ocean surface segment. The camera mounted vehicle also carries positioning tracking system to indicate location of the observed object. But the signal quality is very weak and lost somewhere before reach the control centre. Because GPS signal is unable to penetrate even couple of meters inside the water. So, most of vehicle receiver uses RF and acoustic signal, it can be processed by deployed sensor nodes placed somewhere inside the water to receive the acoustic signal from source localization node. The source localization plays an important role to study abnormal events occurrence especially underwater environment. The global positioning system (GPS) is an accurate location detecting technique which has usage at the earlier stage of underwater VANETs. It has brought out optimal solution to global localization problem, however, it has required large equipment with high installation cost. Thereby, limited number of nodes is involved to detect the location from GPS technology. Due to these, only known network node position can be identified and other unknown nodes are not contributed. The retrieving localization information of known and unknown network nodes from sensitive region has brought out the challenging research topic in an underwater VANET environment. In this research work, developed efficient source localization algorithms which influence distance and angle based algorithms to track the object position and maintain sufficient data transfer between two sensor nodes especially in underwater environment. The modified probability genetic model and graph theoretic approaches were combined to develop algorithms for optimization of above issues in the AUV-aided localization (AAL). Thus, make more accurate and sufficient data transmission among the neighbor's nodes. Thereby, the overall network lifetime and energy efficiency of data transmission has been improved.


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    Title :

    Vision based multi object tracking and localization from autonomous aerial vehicle


    Contributors:
    SHAIK BAZANI (author) / SIROHI SACHIN (author) / NEWARE RAHUL (author) / GOPU V (author) / NAGARAJU A (author) / SHANKAR HATI ANANDA (author) / JANI SUKETU (author) / THAKUR MUKESH (author) / DEEPAK S S K (author) / SHARMA VINOD KUMAR (author)

    Publication date :

    2021-11-25


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    English


    Classification :

    IPC:    G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / B63G OFFENSIVE OR DEFENSIVE ARRANGEMENTS ON VESSELS , Angriffs- oder Verteidigungsanordnungen auf Schiffen / G01S RADIO DIRECTION-FINDING , Funkpeilung / H04B TRANSMISSION , Übertragung



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