Edge-boxes based Convolutional Neural Networks Approach for Multi-Target Tracking in Traffic Scenes
碩士 === 國立清華大學 === 資訊工程學系所 === 105 === Computer vision is important for autonomous cars to detect or track the object nearby such as people, vehicles or animals. However, there are many problems in visual tracking including illumination variation, deformation and occlusion, etc. To deal with these co...
Main Authors: | Lu, Ming-En, 呂明恩 |
---|---|
Other Authors: | Wang, Jia-Shung |
Format: | Others |
Language: | en_US |
Published: |
2017
|
Online Access: | http://ndltd.ncl.edu.tw/handle/rcmks6 |
Similar Items
-
Traffic Scene Depth Analysis Based on Depthwise Separable Convolutional Neural Network
by: Jianzhong Yuan, et al.
Published: (2019-01-01) -
An Adaptive Vehicle Detection Scheme for Urban Traffic Scenes based on Convolutional Neural Networks
by: Dao-Wei Yang, et al.
Published: (2018) -
An Edge Based Visual Tracking System for Target within Complex Environment
by: En-Wei Huang, et al.
Published: (1999) -
Multi-Mode Target Tracking on a Crowd Scene
by: Jian-Cheng Wang, et al.
Published: (2007) -
Multi-scene Image Enhancement for IoT-enabled Edge Cameras
by: Bo-En Shao, et al.
Published: (2019)