Facial Recognition and Customer Behavior Analysis

オープン 投稿 2時間前 着払い 終了日 6 日
オープン 着払い 終了日 6 日

Project Objectives:

The primary goal of this project is to gain insights into customer movement and behavior within the store to measure conversion rates (leads vs. actual buyers) and better understand the target audience.

Project Description:

The system will integrate with the existing CCTV infrastructure (Hikvision DVR) to extract and analyze customer data, providing the following functionalities:

1. Customer Counting:

o Count the number of customers entering the store, excluding employees.

o Avoid duplicate counting of the same customer.

o Generate reports filtering customer traffic by time of day, days of the week, etc.

o Extend this functionality to outdoor cameras to compare passerby traffic with actual store visitors.

2. Demographic Identification:

o Determine customers' gender, estimated age, and racial profile.

o Generate detailed reports to understand customer demographics.

o Include filters for customer type per time of day and days of the week.

3. Emotional Analysis:

o Identify customer emotions upon entering and exiting the store to assess satisfaction levels.

o Integrate emotional analysis with demographic reports.

4. Heatmap Analysis:

o Generate heatmaps highlighting high-traffic areas within the store.

o Estimate the average dwell time in different store sections.

o If feasible, associate detected emotions with specific store areas.

o Provide filters to analyze movement trends per time of day and day of the week.

5. Report Generation:

o Export all collected data into Excel or a similar format for analysis.

o A single report should contain:

 Date

 Unique customer identifier (to accumulate total customer count)

 Gender

 Age estimation

 Entry time

 Entry emotion

 Exit time

 Exit emotion

 Racial profile

o Heatmap reports should display:

 Most frequented store areas

 Average time spent per section

 If applicable, emotional trends per area

Technical Considerations & Open Questions:

• How will the system connect with each store and process video footage?

• Will a dedicated server be required for processing and storage?

• What level of accuracy can be expected for demographic and emotional analysis?

• How will privacy and data protection regulations be handled?

• What is the estimated project timeline?

• How will the payment structure be defined?

Stakeholders:

• Client: Coimbra Pharmacies

Deliverables:

• Customer count analysis tool (Phase 1)

• Heatmap analysis tool (Phase 2)

• Final integrated system with demographic and emotional recognition (Phase 3)

Machine Learning (ML) Deep Learning 人工知能の専門家 OpenCV Python

プロジェクトID: #39048837

プロジェクトについて

17個の提案 入札可能 リモートプロジェクト アクティブ 39 分前

17人のフリーランサーが、平均$23 で、この仕事に入札しています。

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