Object Detection in Videos Using Frame Differencing Method
Implementing object detection in videos through frame differencing technique, currently supports image processing only, requires video-to-image sequence conversion
Object Detection and Image Classification Using Feature Context
The CVPR 2011 paper "Feature Context for Object Detection and Image Classification" by Xinggang Wang and Xiang Bai presents a novel approach for object detection and image classification through feature context utilization, introducing implementation insights for contextual feature extraction and integration algorithms.
Poselet: A Popular Algorithm for Human Body Detection and Pose Estimation
The Poselet algorithm, widely used for human body detection, can also be applied to general object detection with enhanced local feature recognition capabilities.
Simulating Physiological Characteristics of Human Visual System - Visual Attention Mechanism
This folder contains code implementation and corresponding research papers focused on simulating the physiological characteristics of human visual system through visual attention mechanisms. The project detects visually salient objects and regions following human visual observation patterns, and establishes the relationship between saliency density and scale in significant areas. The implementation includes algorithms for bottom-up visual attention modeling, feature extraction, and saliency map generation. Applications span biological vision simulation, visual target detection, visual object tracking, intelligent visual surveillance, as well as research in visual physiology and psychology.
Open Source Implementation of Gentle Boost Algorithm for Object Detection
This is an open-source Gentle Boost implementation written by an international developer, providing foundational code for basic object detection tasks with machine learning approaches.
Open-source Gentel Boost implementation by an international developer
Open-source Gentel Boost implementation by a developer from overseas