New Object Detection, Tracking, and Recognition Approaches for Video Surveillance Over Camera Network


Object detection and tracking are 2 fundamental tasks in multicamera surveillance. This paper proposes a framework for achieving these tasks in a very nonoverlapping multiple camera network. A new object detection algorithm using mean shift (MS) segmentation is introduced, and occluded objects are additional separated with the assistance of depth info derived from stereo vision. The detected objects are then tracked by a replacement object tracking algorithm using a novel Bayesian Kalman filter with simplified Gaussian mixture (BKF-SGM). It employs a Gaussian mixture (GM) illustration of the state and noise densities and a novel direct density simplifying algorithm for avoiding the exponential complexity growth of standard Kalman filters (KFs) using GM. When including an improved MS tracker, a replacement BKF-SGM with improved MS algorithm with a lot of sturdy tracking performance is obtained. Furthermore, a nontraining-based object recognition algorithm is used to support object tracking over nonoverlapping network. Experimental results show that: one) the proposed object detection algorithm yields improved segmentation results over standard object detection ways and a pair of) the proposed tracking algorithm can successfully handle advanced situations with smart performance and low arithmetic complexity. Moreover, the performance of both nontraining- and coaching-based mostly object recognition algorithms will be improved using our detection and tracking results as input.

Did you like this research project?

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

PROJECT TITLE :A new architecture of INC-fuzzy hybrid method for tracking maximumpower purpose in PV cellsABSTRACT:The importance and necessity of energy for human societies are so clear however the traditional sources of energy
PROJECT TITLE :Performance Analysis of a New Calibration Method for Fiber Nonlinearity Compensation - 2018ABSTRACT:Digital signal processing for fiber nonlinearity compensation could be a key enabler for the ever-increasing demand
PROJECT TITLE :New Bound on Partial Hamming Correlation of Low-Hit-Zone Frequency Hopping Sequences and Optimal Constructions - 2018ABSTRACT:During this letter, a brand new bound on partial Hamming correlation (PHC) of low-hit-zone
PROJECT TITLE :New Automatic Modulation Classifier Using Cyclic-Spectrum Graphs With Optimal Training Features - 2018ABSTRACT:A new feature-extraction paradigm for graph-based automatic modulation classification is proposed in
PROJECT TITLE :A New Construction of EVENODD Codes With Lower Computational Complexity - 2018ABSTRACT:EVENODD codes are binary array codes for correcting double disk failures in RAID-half-dozen with asymptotically optimal encoding

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

Project Enquiry