Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Spatio-Temporal Human Activity Recognition using CNN and LSTM

Spatio-Temporal Human Activity Recognition using CNN and LSTM

Acharjya, Pinaki Pratim
Chatterjee, Tarunima

Paperback

Business General

ISBN10: 6209136834
ISBN13: 9786209136832
Publisher: LAP Lambert Academic Publishing
Published: Oct 27 2025
Pages: 68
Weight: 0.23
Height: 0.16 Width: 6.00 Depth: 9.00
Language: English
This book presents a robust Human Activity Recognition (HAR) system that integrates Convolutional Neural Networks (CNNs) with Long Short-Term Memory (LSTM) networks, evaluated on the challenging UCF50 dataset. By combining CNNs' ability to extract spatial features from video frames with LSTMs' strength in modeling temporal sequences, the hybrid model accurately recognizes both simple and complex human actions unfolding over time. This approach addresses key HAR challenges, improving accuracy and generalization across diverse activities. Experimental results demonstrate enhanced precision and stability over conventional models. The system's versatility supports applications in surveillance, healthcare, sports analytics, and human-computer interaction. By bridging spatial and temporal learning, the book offers a scalable, real-world HAR solution adaptable to various environments, laying groundwork for future advances in activity recognition technologies.

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