Image aesthetics have been a popular topic in the recent years. The users can obtain aesthetic score of any image by using the computational approaches based on photography rules. However, most approaches consider the task as an off-line process because those methods usually require high computational complexity. On the other hand, mobile devices (tablet and smart phone) have become an indispensable tool in our daily life. Many users are more willing to take photos with them instead of digital cameras. Thus, developing practical camera applications (APPs) for mobile devices has high application potential. In this paper, respect to the issue of hardware computation limitation of mobile devices, we first design an instant photo aesthetics evaluation method. It adopts several simple and effective features to predict photo scores. The preliminary results conducted on benchmark datasets verify its performance and efficiency. Based on this achievement, we develop a continuous-shot photo recommendation system. It includes two steps: dominant photo selection performed in partially-decoded compression domain and instant photo aesthetics ranking. The system can automatically list the photos with higher scores, and help users to select desired ones. Crowd sourcing tests are employed to evaluate system performance, which show that our system is effective for instant aesthetic rating and photo recommendation.¹

近年来，图像美学已成为热门话题。通过使用基于摄影规则的计算方法，用户可以获取任何图像的美学分数。但是，大多数方法都将任务视为离线过程，因为这些方法通常需要很高的计算复杂度。另一方面，移动设备（平板电脑和智能手机）已成为我们日常生活中必不可少的工具。许多用户更愿意用它们代替数码相机来拍照。因此，开发用于移动设备的实际相机应用（APP）具有很高的应用潜力。本文针对移动设备的硬件计算限制问题，首先设计了一种即时照片美学评估方法。它采用了几种简单有效的功能来预测照片分数。在基准数据集上进行的初步结果验证了其性能和效率。基于这一成就，我们开发了一个连拍照片推荐系统。它包括两个步骤：在部分解码的压缩域中执行占优势的照片选择，以及即时的照片美学排名。系统可以自动列出得分较高的照片，并帮助用户选择所需的照片。通过众包测试来评估系统性能，这表明我们的系统对于即时美学评级和照片推荐非常有效。在部分解码的压缩域中执行主要照片选择，并进行即时照片美学排名。系统可以自动列出得分较高的照片，并帮助用户选择所需的照片。通过众包测试来评估系统性能，这表明我们的系统对于即时美学评级和照片推荐非常有效。在部分解码的压缩域中执行主要照片选择，并进行即时照片美学排名。系统可以自动列出得分较高的照片，并帮助用户选择所需的照片。通过众包测试来评估系统性能，这表明我们的系统对于即时美学评级和照片推荐非常有效。^1个