Feedforward object-vision models only tolerate small image variations compared to human

Feedforward object-vision models only tolerate small image variations compared to human

Invariant object recognition is a remarkable ability of primates' visual system that its underlying mechanism has constantly been under intense investigations. Computational modeling is a valuable tool toward understanding the processes involved in invariant object recognition. Although recent computational models have shown outstanding performances on challenging image databases, they fail to ...

Vision Models and Applications to Image

Human Vision Models for Perceptually Optimized Image Processing – A Review

By taking into account the properties and limitations of the human visual system (HVS), images can be more efficiently compressed, colors more accurately reproduced, prints better rendered, to mention a few major advantages. To achieve these goals it is necessary to build a computational model of the HVS. In this paper we give an introduction to the general issue of HVS-modeling and review the ...

Small Object Detection Based on Stereo Vision*

Sensing the environment around the host vehicle is an essential task of autonomous driving systems and advanced driver assistance systems. Detecting small objects on road is one of the environment sensing tasks which LIDAR has some fundamental difficulties to handle. For example, assume a typical LIDAR, Velodyne HDL-32E, installed on the top of a vehicle with 2.4 meter high. According to the sp...

Human Vision Based Object Recognition

Serre, Wolf, and Poggio introduced an object recognition algorithm that simulates image processing in visual cortex and claimed to get better results than traditional recognition methods. A close examination of their algorithm shows that it is based largely on manually picked parameters. In this project, machine learning methods are applied to modify the algorithm.