Hybrid algorithm for multi people counting and tracking for smart surveillance
Reliable people counting and tracking is active research topic in visual surveillance. In this
work, a novel approach has been proposed for estimating people and tracking their location …
work, a novel approach has been proposed for estimating people and tracking their location …
[PDF][PDF] Early wildfire detection using machine learning model deployed in the fog/edge layers of IoT
The impact of wildfires, even following the fire's extinguishment, continues to affect harmfully
public health and prosperity. Wildfires are becoming increasingly frequent and severe, and …
public health and prosperity. Wildfires are becoming increasingly frequent and severe, and …
Deep understanding of shopper behaviours and interactions using RGB-D vision
In retail environments, understanding how shoppers move about in a store's spaces and
interact with products is very valuable. While the retail environment has several favourable …
interact with products is very valuable. While the retail environment has several favourable …
[HTML][HTML] Embedding AI ethics into the design and use of computer vision technology for consumer's behaviour understanding
Artificial Intelligence (AI) techniques are becoming more and more sophisticated showing
the potential to deeply understand and predict consumer behaviour in a way to boost the …
the potential to deeply understand and predict consumer behaviour in a way to boost the …
Dynamic Kernel CNN-LR model for people counting
People Counting in images is a worthwhile task as it is widely used for public safety,
emergency people planning, intelligent crowd flow, and countless other reasons. Counting …
emergency people planning, intelligent crowd flow, and countless other reasons. Counting …
Crowd Monitoring in Smart Destinations Based on GDPR-Ready Opportunistic RF Scanning and Classification of WiFi Devices to Identify and Classify Visitors' Origins
Crowd monitoring was an essential measure to deal with over-tourism problems in urban
destinations in the pre-COVID era. It will play a crucial role in the pandemic scenario when …
destinations in the pre-COVID era. It will play a crucial role in the pandemic scenario when …
Retail Robot Navigation: A Shopper Behavior-Centric Approach to Path Planning
In the ever-evolving landscape of retail, understanding shopper behavior is pivotal for
optimizing sales and effectively managing product availability and placement. This study …
optimizing sales and effectively managing product availability and placement. This study …
Crowd Counting Model Using Convolutional Neural Network
Crowd Counting is being used for public safety, effective management of the crowd in
elections or pilgrimages, music concerts. Recently there was a stampede in January 2022 in …
elections or pilgrimages, music concerts. Recently there was a stampede in January 2022 in …
A Deep Learning-Based System for Product Recognition in Intelligent Retail Environment
This work proposes a pipeline that aims to recognize the products in a shelf, at the level of
the single SKU (Stock Kee** Unit), starting from a photo of that shelf. It is composed of a …
the single SKU (Stock Kee** Unit), starting from a photo of that shelf. It is composed of a …
Tracking without a Tracker. A Computer Vision Algorithm for Person Counting
Person counting is essential for applications such as store analytics, crowd management,
and COVID-19 prevention. This paper aims to develop a tracking approach that isn't tied to a …
and COVID-19 prevention. This paper aims to develop a tracking approach that isn't tied to a …