Paper Reading AI Learner

Enhanced Consumer Feedback Enabler System for Advertisement Boards using Auto Panning Camera

2020-12-07 10:09:20
Aditya Ajit Khadilkar, Godwyn James William, Hemprasad Yashwant Patil

Abstract

The feedback of consumers who pass by an advertisement board is crucial for the marketing teams of corporate companies .If the emotions of a consumer are analyzed after exposure to the advertisement, it would help to rate the quality of the advertisement .The state of the art emotion analyzers can do this task seamlessly .However, if the consumer moves away from the center of the advertisement board, it becomes difficult for the camera to capture the person with sufficient details .Here, the role of an auto-pan and tilt camera is imminent if a person moves out from the frame limits of the camera .This paper aims to help solve the above issue by panning and tilting the camera by precise amount automatically using facial detection and interpolation algorithms .We propose a method where a camera attached to servo motors can automatically pan and tilt such that the subject is always in the center of the frame .This would be done by facial detection and interpolation of its position with respect to the angle of the camera .The direction of the camera is controlled with the help of a microcontroller, which takes-in the angle values of where the camera needs to move in order to maintain the subject's face in the center .We have designed a system that works on the Arduino platform and can pan and tilt the camera in real-time.

Abstract (translated)

URL

https://arxiv.org/abs/2012.03562

PDF

https://arxiv.org/pdf/2012.03562.pdf


Tags
3D Action Action_Localization Action_Recognition Activity Adversarial Agent Attention Autonomous Bert Boundary_Detection Caption Chat Classification CNN Compressive_Sensing Contour Contrastive_Learning Deep_Learning Denoising Detection Dialog Diffusion Drone Dynamic_Memory_Network Edge_Detection Embedding Embodied Emotion Enhancement Face Face_Detection Face_Recognition Facial_Landmark Few-Shot Gait_Recognition GAN Gaze_Estimation Gesture Gradient_Descent Handwriting Human_Parsing Image_Caption Image_Classification Image_Compression Image_Enhancement Image_Generation Image_Matting Image_Retrieval Inference Inpainting Intelligent_Chip Knowledge Knowledge_Graph Language_Model Matching Medical Memory_Networks Multi_Modal Multi_Task NAS NMT Object_Detection Object_Tracking OCR Ontology Optical_Character Optical_Flow Optimization Person_Re-identification Point_Cloud Portrait_Generation Pose Pose_Estimation Prediction QA Quantitative Quantitative_Finance Quantization Re-identification Recognition Recommendation Reconstruction Regularization Reinforcement_Learning Relation Relation_Extraction Represenation Represenation_Learning Restoration Review RNN Salient Scene_Classification Scene_Generation Scene_Parsing Scene_Text Segmentation Self-Supervised Semantic_Instance_Segmentation Semantic_Segmentation Semi_Global Semi_Supervised Sence_graph Sentiment Sentiment_Classification Sketch SLAM Sparse Speech Speech_Recognition Style_Transfer Summarization Super_Resolution Surveillance Survey Text_Classification Text_Generation Tracking Transfer_Learning Transformer Unsupervised Video_Caption Video_Classification Video_Indexing Video_Prediction Video_Retrieval Visual_Relation VQA Weakly_Supervised Zero-Shot