Golf video tracking based on recognition with HOG and spatial–temporal vector

Action Change Detection in Video Based on HOG

Background and Objectives: Action recognition, as the processes of labeling an unknown action of a query video, is a challenging problem, due to the event complexity, variations in imaging conditions, and intra- and inter-individual action-variability. A number of solutions proposed to solve action recognition problem. Many of these frameworks suppose that each video sequence includes only one ...

An Improved Motion Vector Estimation Approach for Video Error Concealment Based on the Video Scene Analysis

In order to enhance the accuracy of the motion vector (MV) estimation and also reduce the error propagation issue during the estimation, in this paper, a new adaptive error concealment (EC) approach is proposed based on the information extracted from the video scene. In this regard, the motion information of the video scene around the degraded MB is first analyzed to estimate the motion type of...

Warning Traffic Sign Detection Using Learning Vector Quantization & Hough Transform and Recognition Based On HOG

Adaptive Cell-Size HoG Based Object Tracking with Particle Filter

Visual object tracking is one of the most vigorous research area in Computer Vision. A lot of algorithms already achieve high performance and accuracy. Whereas, most of visual object tracking algorithms proceed separately from detection algorithm because of difference between tracking and detection descriptor. Instead, we propose adaptive cell-size HoG (acHoG) based Particle Filter Tracking (PF...

Video-Based Face Recognition and Tracking from a Robot Companion

This paper deals with video-based face recognition and tracking from a camera mounted on a mobile robot companion. All persons must be logically identified before being authorized to interact with the robot while continuous tracking is compulsory in order to estimate the person's approximate position. A first contribution relates to experiments of still-image-based face recognition methods in o...