Multiple Target Tracking Using Cheap Joint Probabilistic Data Association Multiple Model Particle Filter in Sensors Array
نویسندگان
چکیده
منابع مشابه
Multiple Target Tracking Using Cheap Joint Probabilistic Data Association Multiple Model Particle Filter in Sensors Array
Joint multiple target tracking and classification is an important issue in many engineering applications. In recent years, multiple sensor data fusion has been extensively investigated by researchers in a variety of disciplines. Indeed, combining results issued from multiple sensors can provide more accurate information than using a single sensor. In the present paper we address the problem of ...
متن کاملMultiple Body Part Tracking Using a Probabilistic Data Association Filter
This paper presents a framework for multiple body part tracking based on a probabilistic data association (DA) filter. The body parts are extracted using iterative cluster background subtraction and foreground modeling with pictorial structures. The background subtracted silhouette is cluttered and the body parts are subject to occlusions. The main novelty of the paper is in the effective solut...
متن کاملCheap Joint Probabilistic Data Association with Neural Network State Filter for Tracking Multiple Targets in Cluttered Environment
In this paper a cheap joint probabilistic data association (CJPDA) with the neural network state filter (NNSF) is presented for tracking multiple targets in low and high cluttered environments. The state update step of the CJPDA filter (CJPDAF) is realized with the NNSF instead of Kalman filter. Through simulation, a comparison is made to show the performance difference between the CJPDA with N...
متن کاملScheduling Multiple Sensors Using Particle Filters in Target Tracking
A critical component of a multi-sensor system is sensor scheduling to optimize system performance under constraints (e.g. power, bandwidth, and computation). In this paper, we apply particle filter sequential Monte Carlo methods to implement multiple sensor scheduling for target tracking. Under the constraint that only one sensor can be used at each time step, we select a sequence of sensor use...
متن کاملJoint Probabilistic Data Association Filter for Real- Time Multiple Human Tracking in Video
Human tracking in video is required for interactive multimedia, action recognition, and surveillance. Two of the main challenges in tracking are modelling adequately features for tracking and resolving data (measurement) ambiguities in order to map out trajectories. A silhouette based tracker with reduced complexity joint probabilistic data association filter for resolution of measurement-to-tr...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Artificial Intelligence & Applications
سال: 2012
ISSN: 0976-2191
DOI: 10.5121/ijaia.2012.3401