most citedA Fusion Approach for Efficient Human Skin Detection

167 citations · 200 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2014

Detection of Salient Regions in Crowded Scenes

Mei Kuan Lim, Chee Seng Chan, Dorothy Monekosso +1

The increasing number of cameras and a handful of human operators to monitor the video inputs from hundreds of cameras leave the system ill equipped to fulfil the task of detecting…

cs.CV20143 cited

Crowd Saliency Detection via Global Similarity Structure

Mei Kuan Lim, Ven Jyn Kok, Chen Change Loy +1

It is common for CCTV operators to overlook inter- esting events taking place within the crowd due to large number of people in the crowded scene (i.e. marathon, rally). Thus, ther…

cs.CV2014

Enhanced Random Forest with Image/Patch-Level Learning for Image Understanding

Wai Lam Hoo, Tae-Kyun Kim, Yuru Pei +1

Image understanding is an important research domain in the computer vision due to its wide real-world applications. For an image understanding framework that uses the Bag-of-Words…

cs.CV2014167 cited

A Fusion Approach for Efficient Human Skin Detection

Wei Ren Tan, Chee Seng Chan, Pratheepan Yogarajah +1

A reliable human skin detection method that is adaptable to different human skin colours and illu- mination conditions is essential for better human skin segmentation. Even though…

cs.CV201418 cited

Refined Particle Swarm Intelligence Method for Abrupt Motion Tracking

Mei Kuan Lim, Chee Seng Chan, Dorothy Monekosso +1

Conventional tracking solutions are not feasible in handling abrupt motion as they are based on smooth motion assumption or an accurate motion model. Abrupt motion is not subject t…

cs.CV201412 cited

Scene Image is Non-Mutually Exclusive - A Fuzzy Qualitative Scene Understanding

Chern Hong Lim, Anhar Risnumawan, Chee Seng Chan

Ambiguity or uncertainty is a pervasive element of many real world decision making processes. Variation in decisions is a norm in this situation when the same problem is posed to d…