Li L J and Li F F. What, where and who? classifying events by scene and object recognition[C]. Proceedings of the IEEE 11th International Conference on Computer Vision, Rio de Janeiro, Brazil, 2007: 1-8.
|
Lei B, Wang T, Chen S, et al.. Object recognition based on adapative bag of feature and discriminative learning[C]. Proceedings of the 20th IEEE International Conference on Image Processing, Melbourne, Australia, 2013: 3390-3393.
|
Dalal N and Triggs B. Histograms of oriented gradients for human detection[C]. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Diego, USA, 2005, 1: 886-893.
|
Wei D, Zhao Y, Cheng R, et al.. An enhanced histogram of oriented gradient for pedestrian detection[C]. Proceedings of the 4th IEEE International Conference on Intelligent Control and Information Processing, Beijing, China, 2013: 459-463.
|
Felzenszwalb P F, Girshick R B, McAllester D, et al.. Object detection with discriminatively trained part-based models[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010, 32(9): 1627-1645.
|
Ding Y, Zhang J, Li J, et al.. A bag-of-feature model for video semantic annotation[C]. Proceedings of the 6th IEEE International Conference on Image and Graphics, Hefei, China, 2011: 696-701.
|
Huang D K, Chen K Y, and Cheng S C. Video object detection by model-based tracking[C]. Proceedings of the 20th IEEE International Symposium on Circuits and Systems, Beijing, China, 2013: 2384-2387.
|
Blair C, Robertson N M, and Hume D. Characterizing a heterogeneous system for person detection in video using histograms of oriented gradients: power versus speed versus accuracy[J]. IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 2013, 3(2): 236-247.
|
Liu Y, Jang Y, Woo W, et al.. Video-based object recognition using novel set-of-sets representations[C]. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, Columbus, USA, 2014: 533-540.
|
Sharma P, Huang C, and Nevatia R. Unsupervised incremental learning for improved object detection in a video[C]. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Providence, USA, 2012: 3298-3305.
|
Wu Q and Li H. Mode dependent down-sampling and interpolation scheme for high efficiency video coding[J]. Signal Processing: Image Communication, 2013, 28(6): 581-596.
|
Wang T, Chen Y, He Y, et al.. A real-time rate control scheme and hardware implementation for H. 264/AVC
|
encoders[C]. Proceedings of the 5th IEEE International Congress on Image and Signal Processing, Chongqing, China, 2012: 5-9.
|
Felzenszwalb P F and Huttenlocher D P. Pictorial structures for object recognition[J]. International Journal of Computer Vision, 2005, 61(1): 55-79.
|
Felzenszwalb P F, Girshick R B, and McAllester D. Cascade object detection with deformable part models[C]. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, San Francisco, USA, 2010: 2241-2248.
|
Girshick R B, Felzenszwalb P F, and Mcallester D A. Object detection with grammar models[C]. Proceedings of the 25th IEEE Conference on Advances in Neural Information Processing Systems, Granada, Spain, 2011: 442-450.
|
袁武, 林守勋, 牛振东, 等. H. 264/AVC 码率控制优化算法[J]. 计算机学报, 2008, 31(2): 329-339.
|
Yuan W, Lin S X, Niu Z D, et al.. Efficient rate control schemes for H.264/AVC[J]. Chinese Journal of Computers, 2008, 31(2): 329-339.
|
魏江, 刘迪. 基于DM642的X.264编码器优化[J]. 现代电子技术, 2011, 34(14): 68-70.
|
Wei J and Liu D. Optimization of X.264 encoder based on DM642 platform[J]. Modern Electronics Technique, 2011, 34(14): 68-70.
|
Huang Y H, Ou T S, and Su P Y. Perceptual rate distortion optimization using structural similarity index as quality metric[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2010, 20(11): 16141624.
|
Ou T S, Huang Y H, and Chen H H. SSIM-based perceptual rate control for video coding[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2011, 21(5): 682691.
|
Wang R, Huang C, and Chang P. Adaptive downsampling video coding with spatially scalable rate-distortion modeling [J]. IEEE Transactions on Circuits and Systems for Video Technology, 2014, 24(11): 1957-1968.
|