1名社員同行必須の指示をいただいておりますが、日本からは社員を同行させません。Finalistのみの渡航となるため、現地にて彼らをケアする社員を1名アサインいただけないでしょうか？恐らく他国は1名社員をアサインしてるかと思いますので格差が出ないようにしたいです。
カメラから取り込まれた映像から人物顔を検出し、顔部分の映像を解析することにより、人物属性（性別・年代）・感情（笑顔度合い）の推計をします。センサーから出力されるお客様の属性をデータ化し、予測分析モデルを構築。
Rating
50
Translation / English
- Posted at 02 Oct 2014 at 17:54
We have received an instruction for one of our staff to accompany, but no staff come from Japan. As only the finalists come, could you please assign one of your staff to look after them there? I believe one staff is assigned at each of other countries, I would like it to be fair.
By detecting a person's face from the image captured from the camera and by analysing the image of the face part, it estimates the person's attributes (gender, age) and emotions (smile level). Put into data of the attributes of their customers from the output of the sensor, to build a predictive analysis model.
By detecting a person's face from the image captured from the camera and by analysing the image of the face part, it estimates the person's attributes (gender, age) and emotions (smile level). Put into data of the attributes of their customers from the output of the sensor, to build a predictive analysis model.
Rating
52
Translation / English
- Posted at 02 Oct 2014 at 17:54
We have received a request for one accompany employee, but will there are not accompany employees from Japan. As the trip is only for the Finalist, I wonder if you could assign one employee there to take care of them? I think that other countries are also asigning one employee, so it would be better if there are not differences between them.
By detecting a person's face from the image captured by the camera and analyzing the face portion of the image, we estimate the person attributes (gender, age) and emotions (smile level). The attributes of the customers are converted to data to establish a predictive analysis model.
By detecting a person's face from the image captured by the camera and analyzing the face portion of the image, we estimate the person attributes (gender, age) and emotions (smile level). The attributes of the customers are converted to data to establish a predictive analysis model.
★★☆☆☆ 2.0/1
