A visual tracking system for sports video annotation in unconstrained environments

Abstract

A visual tracking system is presented in which a combination of techniques is used to obtain motion features of objects from a video sequence. Further processing of the motion features gives the spatio-temporal trajectories of the objects, that can be used as cues for annotation. The system solves problems found in tracking objects in unconstrained environments, such as in sports games, where there are multiple objects in motion, the camera performs pan, tilt and zoom movements, and there are objects other than the players in the background. Coarse segmentation is performed with multi-class statistical color models, constructed from samples of representative colors of each team. Motion vectors are computed to find region correspondence between consecutive frames. Background elements are eliminated by using camera motion parameters, and other false matches are detected by analyzing motion pattern consistency. Finally, objects are registered by placing windows centered in each tracked region. An experimental realization was used to test the system for tracking players in a soccer game, but it could had also been used for generating annotation cues of videos from other sports as well.

Integrating Occlusion and Illumination Modeling for Object Tracking Using Image Annotation

“…In order for the movement to be persistent, we use optimization. The objective function is defined as: (1) the objective function mentioned is nonlinear, hence taylor expansion is used to linearize the data term followed by the optimization of objective function performed through iterative reweighted least square (IRLS) [5,6] and pyramid based coarse-to-fine search [4,6]. In order to account for the changes in the lighting condition, the images in 1 F and 2 F contain the first and second order derivative of luminance instead of just RGB channels.…”

“…IRLS proposed in [5,6] is used as equivalent to outer and inner fixed-points, together with the coarse-to-fine search [4,6] Same rule can be used to update 2 E . As coarse to fine technique is used for the algorithm, we get two bidirectional flow fields and cropped visible layer masks that exhibit occlusion.…”

“…In order to increase the robustness of the system, the objective functions of flow estimation and flow interpolation are modeled on lagrange's L1 form [1]. Many techniques such as iterative reweighted least square (IRLS) [5,6] and pyramid based coarse-to-fine search [4,6] were used at large for the optimization of these non linear object functions.…”

“…Over the years motion tracking is being applied widely in multiple fields like biomechanics [2], avionics [3], sport analysis [4], medical [5] etc. Despite the ability of the present systems, occlusion, depth variation, and blurriness are some of the issues which can hinder the effective object tracking.…”

Annotation Supported Contour Based Object Tracking With Frame Based Error Analysis

“…Motion tracking has a wide range of applications in different fields, e.g., object tracking, object recognition, advance coding, editing the videos including mosaicking [2]. Over the years motion tracking is being applied widely in the fields of biomechanics [3], avionics [4], sport analysis [5], medical [6] etc. existing in the real world though is a difficult task but plays a pivotal role in designing a model for any algorithm's evaluation.…”