PROJECT TITLE :

Tracking with spatial constrained coding

ABSTRACT:

A video tracking method based on spatial constrained coding (SCC) is proposed in this study. To characterise local image structure information, the dense scale-invariant feature transform (SIFT) descriptor is extracted for each pixel in the image. The proposed tracking method uses SCC model which adopts a new constrained strategy - weighted code, which is achieved by considering the sum of the weighted codes based on grey values of neighbouring pixels and distances between them. The proposed model is able to obtain robust code of corresponding pixels in the frames of complex scenes by taking spatial information into account, which enhances the stability of coding and makes the tracker more robust for object tracking. Twelve challenging sequences involving partial or full occlusion, large pose variation and drastic illumination change are chosen to test the proposed method. The experimental results show the proposed method performs excellent in comparison with other previously proposed trackers.


Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here


PROJECT TITLE : To Predict or to Relay: Tracking Neighbors via Beaconing in Heterogeneous Vehicle Conditions ABSTRACT: Because of the widespread availability of capabilities for vehicular communications, periodic beaconing is
PROJECT TITLE : Robust H∞ Network Observer-Based Attack-Tolerant Path Tracking Control of Autonomous Ground Vehicle ABSTRACT: Under the influence of external disturbance, measurement noise, and actuator/sensor attack signals,
PROJECT TITLE : Real-Time Tracking Algorithm for Aerial Vehicles Using Improved Convolutional Neural Network and Transfer Learning ABSTRACT: A real-time tracking algorithm that makes use of an improved convolutional neural network
PROJECT TITLE : Model-Reference Reinforcement Learning for Collision-Free Tracking Control of Autonomous Surface Vehicles ABSTRACT: In this paper, a novel model-reference reinforcement learning algorithm for intelligent tracking
PROJECT TITLE : RGBT Tracking via Noise-Robust Cross-Modal Ranking ABSTRACT: The currently available RGBT tracking methods usually involve the use of a bounding box to localize a target object. In this method, the trackers are

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry